Irstea Motive - people:maxime.lenormand

M. Lenormand, S. Huet, F. Gargiulo
Generating French virtual commuting networks at the municipality level
Journal of Transport and Land Use, 2014
abs doi web bib

We aim to generate virtual commuting networks in the rural regions of France in order to study the dynamics of their municipalities. Since it will be necessary to model small commuting flows between municipalities with a few hundred or thousand inhabitants, we have opted for the stochastic model presented by Gargiulo et al. (2012). This model reproduces various possible complete networks using an iterative process, stochastically selecting a workplace in the region for each commuter living in the municipality of a region. The choice is made considering the job offers in each municipality of the region and the distance to all of the possible destinations. This paper will present methods for adapting and implementing this model to generate commuting networks between municipalities for regions in France. We address three different issues: How can we generate a reliable virtual commuting network for a region that is highly dependent on other regions for the satisfaction of its residents demands for employment? What about a convenient deterrence function? How can we calibrate the model when detailed data is not available? Our solution proposes an extended job search geographical base for commuters living in the municipalities; we compare two different deterrence functions and we show that the parameter is a constant for network linking municipalities in France.
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@article{PUB00040106, author = {Lenormand, M. and Huet, S. and Gargiulo, F.}, title = {Generating French virtual commuting networks at the municipality level}, title = {Générer les réseaux de navettage français au niveau municipalité}, journal = {Journal of Transport and Land Use}, pages = {13}, url = {http://irsteadoc.irstea.fr/cemoa/PUB00040106 / https://www.jtlu.org/index.php/jtlu/article/view/360}, doi = {http://dx.doi.org/http://dx.doi.org/10.5198/jtlu.v7i1.360}, year = {2014}, affiliation = {IFISC MAJORCA ESP ; IRSTEA CLERMONT FERRAND UR LISC FRA ; UNIVERSITE DE NAMUR NAXYS BEL}, abstract = {We aim to generate virtual commuting networks in the rural regions of France in order to study the dynamics of their municipalities. Since it will be necessary to model small commuting flows between municipalities with a few hundred or thousand inhabitants, we have opted for the stochastic model presented by Gargiulo et al. (2012). This model reproduces various possible complete networks using an iterative process, stochastically selecting a workplace in the region for each commuter living in the municipality of a region. The choice is made considering the job offers in each municipality of the region and the distance to all of the possible destinations. This paper will present methods for adapting and implementing this model to generate commuting networks between municipalities for regions in France. We address three different issues: How can we generate a reliable virtual commuting network for a region that is highly dependent on other regions for the satisfaction of its residents demands for employment? What about a convenient deterrence function? How can we calibrate the model when detailed data is not available? Our solution proposes an extended job search geographical base for commuters living in the municipalities; we compare two different deterrence functions and we show that the parameter is a constant for network linking municipalities in France.}, }
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M. Lenormand, G. Deffuant
Generating a synthetic population of individuals in households: sample-free vs sample-based methods
JASSS-The Journal of Artificial Societies and Social Simulation 16 (1), 2013
abs web bib

We compare a sample-free method proposed by Gargiulo et al. (2010) and a sample-based method proposed by Ye et al. (2009) for generating a synthetic population, organised in households, from various statistics. We generate a reference population for a French region including 1310 municipalities and measure how both methods approximate it from a set of statistics derived from this reference population. We also perform a sensitivity analysis. The sample-free method better fits the reference distributions of both individuals and households. It is also less data demanding but it requires more pre-processing. The quality of the results for the sample-based method is highly dependent on the quality of the initial sample.
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@article{PUB00039366, author = {Lenormand, M. and Deffuant, G.}, title = {Generating a synthetic population of individuals in households: sample-free vs sample-based methods }, journal = {JASSS-The Journal of Artificial Societies and Social Simulation}, volume = {16}, number = {1}, url = {http://irsteadoc.irstea.fr/cemoa/PUB00039366 / http://jasss.soc.surrey.ac.uk/16/4/12.html}, year = {2013}, affiliation = {IRSTEA CLERMONT FERRAND UR LISC FRA ; IRSTEA CLERMONT FERRAND UR LISC FRA}, abstract = {We compare a sample-free method proposed by Gargiulo et al. (2010) and a sample-based method proposed by Ye et al. (2009) for generating a synthetic population, organised in households, from various statistics. We generate a reference population for a French region including 1310 municipalities and measure how both methods approximate it from a set of statistics derived from this reference population. We also perform a sensitivity analysis. The sample-free method better fits the reference distributions of both individuals and households. It is also less data demanding but it requires more pre-processing. The quality of the results for the sample-based method is highly dependent on the quality of the initial sample.}, }
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M. Lenormand, F. Jabot, G. Deffuant
Adaptive approximate Bayesian computation for complex models
Computational Statistics 28 (6), 2013
abs doi web bib

We propose a new approximate Bayesian computation (ABC) algorithm that aims at minimizing the number of model runs for reaching a given quality of the posterior approximation. This algorithm automatically determines its sequence of tolerance levels and makes use of an easily interpretable stopping criterion. Moreover, it avoids the problem of particle duplication found when using a MCMC kernel. When applied to a toy example and to a complex social model, our algorithm is 2–8 times faster than the three main sequential ABC algorithms currently available.
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@article{PUB00038699, author = {Lenormand, M. and Jabot, F. and Deffuant, G.}, title = {Adaptive approximate Bayesian computation for complex models}, title = {Algorithme adaptatif de computation byésienne approchée pour des modèles complexes}, journal = {Computational Statistics}, volume = {28}, number = {6}, pages = {2777-2796}, url = {http://irsteadoc.irstea.fr/cemoa/PUB00038699 / http://link.springer.com/article/10.1007%2Fs00180-013-0428-3}, doi = {http://dx.doi.org/10.1007/s00180-013-0428-3}, year = {2013}, affiliation = {IRSTEA CLERMONT FERRAND UR LISC FRA ; IRSTEA CLERMONT FERRAND UR LISC FRA ; IRSTEA CLERMONT FERRAND UR LISC FRA}, abstract = {We propose a new approximate Bayesian computation (ABC) algorithm that aims at minimizing the number of model runs for reaching a given quality of the posterior approximation. This algorithm automatically determines its sequence of tolerance levels and makes use of an easily interpretable stopping criterion. Moreover, it avoids the problem of particle duplication found when using a MCMC kernel. When applied to a toy example and to a complex social model, our algorithm is 2–8 times faster than the three main sequential ABC algorithms currently available.}, }
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F. Gargiulo, M. Lenormand, S. Huet, O. Baqueiro Espinosa
Commuting network models: Getting the essentials
JASSS-The Journal of Artificial Societies and Social Simulation 15 (2), 2012
abs web bib

Human mobility and, in particular, commuting patterns have a fundamental role in understanding socio-economic systems. Analysing and modelling the networks formed by commuters, for example, has become a crucial requirement in studying rural areas dynamics and to help decision-making. This paper presents a simple spatial interaction commuting model with only one parameter. The proposed algorithm considers each individual who wants to commute, starting from their residence to all the possible workplaces. The algorithm decides the location of the workplace following the classical rule inspired from the gravity law consisting of a compromise between the job offers and the distance to the job. The further away the job is, the more important the offer should be to be considered for the decision. Inversely, the quantity of offers is not important for the decision when these offers are close by. The presented model provides a simple, yet powerful approach to simulate realistic distributions of commuters for empirical studies with limited data availability. The paper also presents a comparative analysis of the structure of the commuting networks of the four European regions to which we apply our model. The model is calibrated and validated on these regions. The results from the analysis show that the model is very efficient in reproducing most of the statistical properties of the network given by the data sources.
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@article{PUB00035312, author = {Gargiulo, F. and Lenormand, M. and Huet, S. and Baqueiro Espinosa, O.}, title = {Commuting network models: Getting the essentials }, title = {Modèle de réseau de navettage: allons à l'essentiel}, journal = {JASSS-The Journal of Artificial Societies and Social Simulation}, volume = {15}, number = {2}, pages = {6}, url = {http://irsteadoc.irstea.fr/cemoa/PUB00035312 / http://jasss.soc.surrey.ac.uk/15/2/6.html}, year = {2012}, affiliation = {IRSTEA CLERMONT FERRAND UR LISC FRA ; IRSTEA CLERMONT FERRAND UR LISC FRA ; IRSTEA CLERMONT FERRAND UR LISC FRA ; LEIBNIZ INSTITUTE FOR AGRICULTURAL DEVELOPMENT IN CENTRAL AND EASTERN EUROPE IAMO DEU}, abstract = {Human mobility and, in particular, commuting patterns have a fundamental role in understanding socio-economic systems. Analysing and modelling the networks formed by commuters, for example, has become a crucial requirement in studying rural areas dynamics and to help decision-making. This paper presents a simple spatial interaction commuting model with only one parameter. The proposed algorithm considers each individual who wants to commute, starting from their residence to all the possible workplaces. The algorithm decides the location of the workplace following the classical rule inspired from the gravity law consisting of a compromise between the job offers and the distance to the job. The further away the job is, the more important the offer should be to be considered for the decision. Inversely, the quantity of offers is not important for the decision when these offers are close by. The presented model provides a simple, yet powerful approach to simulate realistic distributions of commuters for empirical studies with limited data availability. The paper also presents a comparative analysis of the structure of the commuting networks of the four European regions to which we apply our model. The model is calibrated and validated on these regions. The results from the analysis show that the model is very efficient in reproducing most of the statistical properties of the network given by the data sources. }, }
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M. Lenormand, S. Huet, F. Gargiulo, G. Deffuant
A universal model of commuting networks
PLoS One 7 (10), 2012
abs doi web bib

We show that a recently proposed model generates accurate commuting networks on 80 case studies from different regions of the world (Europe and United-States) at different scales (e.g. municipalities, counties, regions). The model takes as input the number of commuters coming in and out of each geographic unit and generates the matrix of commuting flows between the units. The single parameter of the model follows a universal law that depends only on the scale of the geographic units. We show that our model significantly outperforms two other approaches proposing a universal commuting model (Balcan et al. (2009); Simini et al. (2012)), particularly when the geographic units are small (e.g. municipalities).
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@article{PUB00036161, author = {Lenormand, M. and Huet, S. and Gargiulo, F. and Deffuant, G.}, title = {A universal model of commuting networks}, title = {Un modèle universel de réseaux de navettage}, journal = {PLoS One}, volume = {7}, number = {10}, pages = {11}, url = {http://irsteadoc.irstea.fr/cemoa/PUB00036161 / http://www.plosone.org}, doi = {http://dx.doi.org/10.1371/journal.pone.0045985}, year = {2012}, affiliation = {IRSTEA CLERMONT FERRAND UR LISC FRA ; IRSTEA CLERMONT FERRAND UR LISC FRA ; CNRS PARIS FRA ; IRSTEA CLERMONT FERRAND UR LISC FRA}, abstract = {We show that a recently proposed model generates accurate commuting networks on 80 case studies from different regions of the world (Europe and United-States) at different scales (e.g. municipalities, counties, regions). The model takes as input the number of commuters coming in and out of each geographic unit and generates the matrix of commuting flows between the units. The single parameter of the model follows a universal law that depends only on the scale of the geographic units. We show that our model significantly outperforms two other approaches proposing a universal commuting model (Balcan et al. (2009); Simini et al. (2012)), particularly when the geographic units are small (e.g. municipalities).}, }
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M. Lenormand, S. Huet, G. Deffuant
Deriving the number of jobs in proximity services from the number of inhabitants in french rural municipalities
PLoS One 7 (7), 2012
abs doi web bib

We use a minimum requirement approach to derive the number of jobs in proximity services per inhabitant in French rural municipalities. We first classify the municipalities according to their time distance in minutes by car to the municipality where the inhabitants go the most frequently to get services (called MFM). For each set corresponding to a range of time distance to MFM, we perform a quantile regression estimating the minimum number of service jobs per inhabitant that we interpret as an estimation of the number of proximity jobs per inhabitant. We observe that the minimum number of service jobs per inhabitant is smaller in small municipalities. Moreover, for municipalities of similar sizes, when the distance to the MFM increases, the number of jobs of proximity services per inhabitant increases.
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@article{PUB00035599, author = {Lenormand, M. and Huet, S. and Deffuant, G.}, title = {Deriving the number of jobs in proximity services from the number of inhabitants in french rural municipalities}, title = {Déterminer le nombre d'emplois dans les services de proximité en fonction du nombre d'habitants dans les municipalités rurales françaises}, journal = {PLoS One}, volume = {7}, number = {7}, pages = {8}, url = {http://irsteadoc.irstea.fr/cemoa/PUB00035599 / http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0040001}, doi = {http://dx.doi.org/10.1371/journal.pone.0040001}, year = {2012}, affiliation = {IRSTEA CLERMONT FERRAND UR LISC FRA ; IRSTEA CLERMONT FERRAND UR LISC FRA ; IRSTEA CLERMONT FERRAND UR LISC FRA}, abstract = {We use a minimum requirement approach to derive the number of jobs in proximity services per inhabitant in French rural municipalities. We first classify the municipalities according to their time distance in minutes by car to the municipality where the inhabitants go the most frequently to get services (called MFM). For each set corresponding to a range of time distance to MFM, we perform a quantile regression estimating the minimum number of service jobs per inhabitant that we interpret as an estimation of the number of proximity jobs per inhabitant. We observe that the minimum number of service jobs per inhabitant is smaller in small municipalities. Moreover, for municipalities of similar sizes, when the distance to the MFM increases, the number of jobs of proximity services per inhabitant increases.}, }
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S. Huet, M. Lenormand, G. Deffuant, F. Gargiulo
Parameterisation of individual working dynamics
Empirical Agent-Based Modelling – Challenges and Solutions. Volume 1, The Characterisation and Parameterisation of Empirical Agent-Based Models (p. 133-169), Springer, New York, USA, 2014
abs doi web bib

During the PRIMA European project, we conceived a conceptual model dedicated to the study of the evolution of the European Rural Areas in terms of demography and occupation of their populations. This is a hybrid agent-microsimulation model considering inhabitants as the basic elements composing in households. On the other hand, municipalities are the basic spatial element and the providers for employment and housings. This chapter presents the main objects and their relationships are identified as a first generic way to parameterize the dynamics of such a conceptual model for an implementation of a European region. This chapter explains how dynamics can be parameterised from data for an implementation for a French region. It focusses on the dynamics of work statuses and professions which can be derived from the European Labour Force Survey (LFS). The individual is considered from her entering on the labour market until the moment she decides to retire. Meanwhile, she can be fired, searching for a job when she is unemployed or already employed but also deciding becoming inactive for a while. Jobs are defined by a profession and an activity sector. The job offer is located at the municipality level and can correspond to the searched profession of an individual having a municipality of residence. The French implementation is described starting from the employment survey in France, which is the French declination of the LFS.
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@book{PUB00039099, author = {Huet, S. and Lenormand, M. and Deffuant, G. and Gargiulo, F.}, author = {Smajgl, A. and Barreteau, O.}, title = {Parameterisation of individual working dynamics}, title = {Paramétrisation de la dynamique individuelle relative au travail}, bookTitle = {Empirical Agent-Based Modelling – Challenges and Solutions. Volume 1, The Characterisation and Parameterisation of Empirical Agent-Based Models}, address = {New York, USA}, publisher = {Springer}, pages = {133-169}, url = {http://irsteadoc.irstea.fr/cemoa/PUB00039099}, doi = {http://dx.doi.org/10.1007/978-1-4614-6134-0_8}, year = {2014}, affiliation = {IRSTEA CLERMONT FERRAND UR LISC FRA ; IRSTEA CLERMONT FERRAND UR TSCF FRA ; IRSTEA CLERMONT FERRAND UR LISC FRA ; IRSTEA CLERMONT FERRAND UR LISC FRA}, ISBNISSN = {ISBN 978-1-4614-6133-3}, abstract = {During the PRIMA European project, we conceived a conceptual model dedicated to the study of the evolution of the European Rural Areas in terms of demography and occupation of their populations. This is a hybrid agent-microsimulation model considering inhabitants as the basic elements composing in households. On the other hand, municipalities are the basic spatial element and the providers for employment and housings. This chapter presents the main objects and their relationships are identified as a first generic way to parameterize the dynamics of such a conceptual model for an implementation of a European region. This chapter explains how dynamics can be parameterised from data for an implementation for a French region. It focusses on the dynamics of work statuses and professions which can be derived from the European Labour Force Survey (LFS). The individual is considered from her entering on the labour market until the moment she decides to retire. Meanwhile, she can be fired, searching for a job when she is unemployed or already employed but also deciding becoming inactive for a while. Jobs are defined by a profession and an activity sector. The job offer is located at the municipality level and can correspond to the searched profession of an individual having a municipality of residence. The French implementation is described starting from the employment survey in France, which is the French declination of the LFS.}, }
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M. Lenormand, S. Huet, G. Deffuant, F. Gargiulo
University laws in commuting flows
2013
abs web bib

We propose an individual based model to generate commuting networks from data giving numbers of in and out commuters of every locations of a region. It is inspired from the gravity model. We exhibit from the calibration of 80 various case studies that the only remaining parameter can be suppressed since it follows a law depending on the average surface of the locations. We compare our model to the only one other universal existing approach (Simini et al, 2012) at various scales. We show our model performs better for small locations (in terms of surface and/or number of inhabitants).
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@inproceedings{PUB00039558, author = {Lenormand, M. and Huet, S. and Deffuant, G. and Gargiulo, F.}, title = {University laws in commuting flows}, pages = {1}, url = {http://irsteadoc.irstea.fr/cemoa/PUB00039558}, year = {2013}, affiliation = {IFISC PALMA DE MALLORCA ESP ; IRSTEA CLERMONT FERRAND UR LISC FRA ; IRSTEA CLERMONT FERRAND UR LISC FRA ; NAXYS UNAMUR NAMUR BEL}, abstract = {We propose an individual based model to generate commuting networks from data giving numbers of in and out commuters of every locations of a region. It is inspired from the gravity model. We exhibit from the calibration of 80 various case studies that the only remaining parameter can be suppressed since it follows a law depending on the average surface of the locations. We compare our model to the only one other universal existing approach (Simini et al, 2012) at various scales. We show our model performs better for small locations (in terms of surface and/or number of inhabitants).}, }
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M. Lenormand, F. Jabot, G. Deffuant
Adaptive approximate Bayesian computation for complex models
8th World Congress in Probability and Statistics, 09/07/2012-14/07/2012, Istanbul, TUR (p. 11), 2012
abs web bib

Approximate Bayesian computation (ABC) is a family of computational techniques in Bayesian statistics. These techniques allow to fit a model to data without relying on the computation of the model likelihood. They instead require to simulate a large number of times the model to be fitted. A number of refinements to the original rejection-based ABC scheme have been proposed, including the sequential improvement of posterior distributions. This technique allows to decrease the number of model simulations required, but it still presents several shortcomings which are particularly problematic for costly to simulate complex models. We here provide a new algorithm to perform adaptive approximate Bayesian computation. We present a modification of the PMC-ABC algorithm proposed by Beaumont et al. (2009). We compare this new algorithm with the population Monte Carlo ABC algorithm of Beaumont et al. (2009), the replenishment SMC ABC algorithm of Drovandi and Pettitt (2011) and the adaptive SMC ABC algorithm of DelMoral et al. (2011) on a toy example. Finally, we apply our new algorithm to a complex individual-based social model, the PRIMA model. We show that our algorithm outperforms the three other algorithms in the two applications by requiring less simulations to reach the same posterior density quality.
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@inproceedings{PUB00035693, author = {Lenormand, M. and Jabot, F. and Deffuant, G.}, title = {Adaptive approximate Bayesian computation for complex models}, title = {Calcul Bayésien adaptatif pour les modèles complexes}, bookTitle = {8th World Congress in Probability and Statistics, 09/07/2012-14/07/2012, Istanbul, TUR}, pages = {11}, url = {http://irsteadoc.irstea.fr/cemoa/PUB00035693}, year = {2012}, affiliation = {IRSTEA CLERMONT FERRAND UR LISC FRA ; IRSTEA CLERMONT FERRAND UR LISC FRA ; IRSTEA CLERMONT FERRAND UR LISC FRA}, abstract = {Approximate Bayesian computation (ABC) is a family of computational techniques in Bayesian statistics. These techniques allow to fit a model to data without relying on the computation of the model likelihood. They instead require to simulate a large number of times the model to be fitted. A number of refinements to the original rejection-based ABC scheme have been proposed, including the sequential improvement of posterior distributions. This technique allows to decrease the number of model simulations required, but it still presents several shortcomings which are particularly problematic for costly to simulate complex models. We here provide a new algorithm to perform adaptive approximate Bayesian computation. We present a modification of the PMC-ABC algorithm proposed by Beaumont et al. (2009). We compare this new algorithm with the population Monte Carlo ABC algorithm of Beaumont et al. (2009), the replenishment SMC ABC algorithm of Drovandi and Pettitt (2011) and the adaptive SMC ABC algorithm of DelMoral et al. (2011) on a toy example. Finally, we apply our new algorithm to a complex individual-based social model, the PRIMA model. We show that our algorithm outperforms the three other algorithms in the two applications by requiring less simulations to reach the same posterior density quality.}, }
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M. Lenormand, F. Jabot, G. Deffuant
Adaptive approximate bayesian computation for complex models
The 11th World Meeting of The International Society for Bayesian Analysis (ISBA2012), 25/06/2012-29/06/2012, Kyoto, JPN , 2012
abs web bib

Approximate Bayesian computation (ABC) is a family of computational techniques in Bayesian statistics. These techniques allow to fit a model to data without relying on the computation of the model likelihood. They instead require to simulate a large number of times the model to be fitted. A number of refinements to the original rejection-based ABC scheme have been proposed, including the sequential improvement of posterior distributions. This technique allows to decrease the number of model simulations required, but it still presents several shortcomings which are particularly problematic for costly to simulate complex models. We here provide a new algorithm to perform adaptive approximate Bayesian computation. We present a modification of the PMC-ABC algorithm proposed by (Beaumont et al., 2009). We compare this new algorithm with the population Monte Carlo ABC algorithm of Beaumont et al. (2009), the replenishment SMC ABC algorithm of Drovandi & Pettitt (2011) and the adaptive SMC ABC algorithm of DelMoral et al. (2011) on a toy example. Finally, we apply our new algorithm to a complex individual-based social model, the PRIMA model. We show that our algorithm outperforms the three other algorithms in the two applications by requiring less simulations to reach the same posterior density quality.
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@inproceedings{PUB00035591, author = {Lenormand, M. and Jabot, F. and Deffuant, G.}, title = {Adaptive approximate bayesian computation for complex models}, title = {Calcul Bayésien approché adaptatif pour les modèles complexes}, bookTitle = {The 11th World Meeting of The International Society for Bayesian Analysis (ISBA2012), 25/06/2012-29/06/2012, Kyoto, JPN}, url = {http://irsteadoc.irstea.fr/cemoa/PUB00035591}, year = {2012}, affiliation = {IRSTEA CLERMONT FERRAND UR LISC FRA ; IRSTEA CLERMONT FERRAND UR LISC FRA ; IRSTEA CLERMONT FERRAND UR LISC FRA}, abstract = {Approximate Bayesian computation (ABC) is a family of computational techniques in Bayesian statistics. These techniques allow to fit a model to data without relying on the computation of the model likelihood. They instead require to simulate a large number of times the model to be fitted. A number of refinements to the original rejection-based ABC scheme have been proposed, including the sequential improvement of posterior distributions. This technique allows to decrease the number of model simulations required, but it still presents several shortcomings which are particularly problematic for costly to simulate complex models. We here provide a new algorithm to perform adaptive approximate Bayesian computation. We present a modification of the PMC-ABC algorithm proposed by (Beaumont et al., 2009). We compare this new algorithm with the population Monte Carlo ABC algorithm of Beaumont et al. (2009), the replenishment SMC ABC algorithm of Drovandi & Pettitt (2011) and the adaptive SMC ABC algorithm of DelMoral et al. (2011) on a toy example. Finally, we apply our new algorithm to a complex individual-based social model, the PRIMA model. We show that our algorithm outperforms the three other algorithms in the two applications by requiring less simulations to reach the same posterior density quality.}, }
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S. Huet, M. Lenormand, G. Deffuant
Modelling a network of rural municipalities
ESSA 2011, 19/09/2011-23/09/2011, Montpellier, FRA , 2011
abs web bib

The poster describes the dynamics of individuals changing activities and status on the labour market in a large individual-based model simulating the rural municipalities. Some results are presented for seven municipalities of the French Cantal department. / Ce poster décrit la dynamique d'activité des individus du modèle PRIMA dédié à la modélisation des municipalités rurales.
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@inproceedings{PUB00033512, author = {Huet,S. and Lenormand,M. and Deffuant,G.}, title = {Modelling a network of rural municipalities }, title = {La modélisation d'un réseau de municipalités rurales}, bookTitle = {ESSA 2011, 19/09/2011-23/09/2011, Montpellier, FRA}, url = {http://irsteadoc.irstea.fr/cemoa/PUB00033512}, year = {2011}, affiliation = {CEMAGREF CLERMONT FERRAND UR LISC FRA ; CEMAGREF CLERMONT FERRAND UR LISC FRA ; CEMAGREF CLERMONT FERRAND UR LISC FRA}, abstract = {The poster describes the dynamics of individuals changing activities and status on the labour market in a large individual-based model simulating the rural municipalities. Some results are presented for seven municipalities of the French Cantal department. / Ce poster décrit la dynamique d'activité des individus du modèle PRIMA dédié à la modélisation des municipalités rurales.}, }
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M. Lenormand, G. Deffuant, S. Huet
A commuting generation model requiring only aggregated data
7th European Social Simulation Association Conference, 19/09/2011-23/09/2011, Montpellier, FRA (p. 16), 2011
abs web bib

We recently proposed, in (Gargiulo et al., 2011), an innovative stochastic model with only one parameter to calibrate. It reproduces the complete network by an iterative process stochastically choosing, for each commuter living in the municipality of a region, a workplace in the region. The choice is done considering the job offer in each municipality of the region and the distance to all the possible destinations. The model is quite effective if the region is sufficiently autonomous in terms of job offers. However, calibrating or being sure of this autonomy require data or expertise which are not necessarily available. Moreover the region can be not autonomous. In the present, we overcome these limitations, extending the job search geographical base of the commuters to the outside of the region, and changing the deterrence function form. We also found a law to calibrate the improvement model which does not require data.
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@inproceedings{PUB00033826, author = {Lenormand, M. and Deffuant, G. and Huet, S.}, title = {A commuting generation model requiring only aggregated data}, title = {Un modèle de génération de réseau de navettage nécessitant uniquement des données agrégées}, bookTitle = {7th European Social Simulation Association Conference, 19/09/2011-23/09/2011, Montpellier, FRA}, pages = {16}, url = {http://irsteadoc.irstea.fr/cemoa/PUB00033826}, year = {2011}, affiliation = {CEMAGREF CLERMONT FERRAND UR LISC FRA ; CEMAGREF CLERMONT FERRAND UR LISC FRA ; CEMAGREF CLERMONT FERRAND UR LISC FRA}, abstract = {We recently proposed, in (Gargiulo et al., 2011), an innovative stochastic model with only one parameter to calibrate. It reproduces the complete network by an iterative process stochastically choosing, for each commuter living in the municipality of a region, a workplace in the region. The choice is done considering the job offer in each municipality of the region and the distance to all the possible destinations. The model is quite effective if the region is sufficiently autonomous in terms of job offers. However, calibrating or being sure of this autonomy require data or expertise which are not necessarily available. Moreover the region can be not autonomous. In the present, we overcome these limitations, extending the job search geographical base of the commuters to the outside of the region, and changing the deterrence function form. We also found a law to calibrate the improvement model which does not require data.}, }
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M. Lenormand, G. Deffuant, S. Huet
Calibrating a complex social model
European Conference on Complex Systems ECCS'11, 12/09/2011-16/09/2011, Vienne, AUT , 2011
abs web bib

Approximate Bayesian computation is a family of computational techniques in Bayesian statistics. These techniques allow to fit a model to data without relying on the computation of the model likelihood. A number of improvements to the original ABC scheme have been proposed to speed it up. They include the coupling to Markov chain Monte Carlo to explore the parameter space and the sequential improvement of posterior distributions inspired by sequential Monte Carlo methods. These algorithms present severals shortcomings which are particularly problematic for costly to simulate complex models. In this article an adaptive appoximate Bayesian computation for complex models is proposed which offers improvements to circumvent the limitations of the application of the ABC methods to complex models. We demonstrate our algorithm on a toy example and on a complex social model, the PRIMA model.
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@inproceedings{PUB00033827, author = {Lenormand, M. and Deffuant, G. and Huet, S.}, title = {Calibrating a complex social model}, title = {Calibration d'un modèle social complexe}, bookTitle = {European Conference on Complex Systems ECCS'11, 12/09/2011-16/09/2011, Vienne, AUT}, url = {http://irsteadoc.irstea.fr/cemoa/PUB00033827}, year = {2011}, affiliation = {CEMAGREF CLERMONT FERRAND UR LISC FRA ; CEMAGREF CLERMONT FERRAND UR LISC FRA ; CEMAGREF CLERMONT FERRAND UR LISC FRA}, abstract = {Approximate Bayesian computation is a family of computational techniques in Bayesian statistics. These techniques allow to fit a model to data without relying on the computation of the model likelihood. A number of improvements to the original ABC scheme have been proposed to speed it up. They include the coupling to Markov chain Monte Carlo to explore the parameter space and the sequential improvement of posterior distributions inspired by sequential Monte Carlo methods. These algorithms present severals shortcomings which are particularly problematic for costly to simulate complex models. In this article an adaptive appoximate Bayesian computation for complex models is proposed which offers improvements to circumvent the limitations of the application of the ABC methods to complex models. We demonstrate our algorithm on a toy example and on a complex social model, the PRIMA model.}, }
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M. Lenormand, F. Garguilo, S. Huet
From the Auvergne commuting network to every commuting network
European Conference on Complex Systems ECCS'10 , 13/09/2010-17/09/2010, Lisbonne, PRT , 2010
web bib

@inproceedings{PUB00030598, author = {Lenormand, M. and Garguilo, F. and Huet, S.}, title = {From the Auvergne commuting network to every commuting network}, title = {Réseaux de navettage et caractérisation des communes}, bookTitle = {European Conference on Complex Systems ECCS'10 , 13/09/2010-17/09/2010, Lisbonne, PRT}, url = {http://irsteadoc.irstea.fr/cemoa/PUB00030598 / http://www.eccs2010.eu/postersdemos}, year = {2010}, affiliation = {CEMAGREF CLERMONT FERRAND UR LISC FRA ; CEMAGREF CLERMONT FERRAND UR LISC FRA ; CEMAGREF CLERMONT FERRAND UR LISC FRA}, abstract = {}, }
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M. Lenormand, S. Huet, G. Deffuant
Predicting the presence and the number of jobs in different services in Auvergne municipalities
2010
abs web bib

Nous décrivons dans ce rapport une méthode permettant de prédire la présence de différents services (école, boulangerie...) dans une commune en fonction des caractéristiques de celle-ci. Nous présentons aussi une méthode permettant de prédire le nombre d'emplois dans différentes sortes de services. Les deux méthodes sont testées sur les communes d'Auvergne.
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@misc{PUB00035311, note = {Autres}, author = {Lenormand, M. and Huet, S. and Deffuant, G.}, title = {Predicting the presence and the number of jobs in different services in Auvergne municipalities}, title = {Prédire la présence et le nombre d'emplois dans les services pour les communes d'Auvergne}, pages = {9}, url = {http://irsteadoc.irstea.fr/cemoa/PUB00035311}, year = {2010}, affiliation = {CEMAGREF CLERMONT FERRAND UR LISC FRA ; CEMAGREF CLERMONT FERRAND UR LISC FRA ; CEMAGREF CLERMONT FERRAND UR LISC FRA}, abstract = {Nous décrivons dans ce rapport une méthode permettant de prédire la présence de différents services (école, boulangerie...) dans une commune en fonction des caractéristiques de celle-ci. Nous présentons aussi une méthode permettant de prédire le nombre d'emplois dans différentes sortes de services. Les deux méthodes sont testées sur les communes d'Auvergne.}, }
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S. Huet, N. Dumoulin, G. Deffuant, F. Gargiulo, M. Lenormand, O. Baqueiro Espinosa, S. Ternes
Micro-simulation model of municipality network in the Auvergne case study
2012
abs web bib

How do European rural areas evolve? Some tend to decrease dramatically, as in the Netherlands or in the United Kingdom, where the urban areas tend to spread all over the country. Their population can also be drastically depleting through a large rural exodus, as observed in for instance France, Bulgaria or Croatia in the first part of the last Century. They can also keep steady population densities occupied in leisure services offered to urban people and agriculture with various proportions of inhabitants commuting to the cities for their work. Better understanding these evolutions is what the PRIMA simulation model presented in this report is interested in. / Ce document décrit un modèle de micro-simulation de communes développé dans le cadre du projet européen PRIMA (EU ENV 2007-1). Ce modèle permet d'étudier l'évolution des populations rurales sous l'effet des interactions spatiales et des dynamiques économiques locales.
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@techreport{PUB00036510, author = {Huet, S. and Dumoulin, N. and Deffuant, G. and Gargiulo, F. and Lenormand, M. and Baqueiro Espinosa, O. and Ternes, S.}, title = {Micro-simulation model of municipality network in the Auvergne case study }, title = {Modèle de micro-simulation d'un réseau de communes : étude de cas en Auvergne}, pages = {66}, url = {http://irsteadoc.irstea.fr/cemoa/PUB00036510}, year = {2012}, affiliation = {IRSTEA CLERMONT FERRAND UR LISC FRA ; IRSTEA CLERMONT FERRAND UR LISC FRA ; IRSTEA CLERMONT FERRAND UR LISC FRA ; IRSTEA CLERMONT FERRAND UR LISC FRA ; IRSTEA CLERMONT FERRAND UR LISC FRA ; IAMO INSTITUTE OF AGRICULTURAL DEVELOPMENT IN CENTRAL AND EASTERN EUROPE LEIBNITZ DEU ; IAMO INSTITUTE OF AGRICULTURAL DEVELOPMENT IN CENTRAL AND EASTERN EUROPE LEIBNITZ DEU}, abstract = {How do European rural areas evolve? Some tend to decrease dramatically, as in the Netherlands or in the United Kingdom, where the urban areas tend to spread all over the country. Their population can also be drastically depleting through a large rural exodus, as observed in for instance France, Bulgaria or Croatia in the first part of the last Century. They can also keep steady population densities occupied in leisure services offered to urban people and agriculture with various proportions of inhabitants commuting to the cities for their work. Better understanding these evolutions is what the PRIMA simulation model presented in this report is interested in. / Ce document décrit un modèle de micro-simulation de communes développé dans le cadre du projet européen PRIMA (EU ENV 2007-1). Ce modèle permet d'étudier l'évolution des populations rurales sous l'effet des interactions spatiales et des dynamiques économiques locales.}, }
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N. Turpin, B. Hautdidier, R. Laplana, D. Kopeva, M. Raley, O. Baqueiro, G. Deffuant, G. Woltjer, B. Meyer, M. Njavro, L. Jelinek, G. Abrami, O. Aznar, O. Barreteau, I. Bezlepkina, A. Bouwman, R. Franic, G. Garrod, M. Gomez, Wander Jager, S. Huet, E. Kozáková, M. Lenormand, J.B. Marsat, M. Delin, E. Perret, K. Rodseth, E. Romstad, B. ¦akic Bobic, F. Schaft, H. Talbot, Q. Zhang
Final Report D0.4, PRIMA collaborative project, EU 7th Framework Programme, contract no. 212345
2012
abs web bib

Facing structural change, European rural areas still fulfil multiple social, economic and ecological functions. Because of scale interplays and sustainability trade-offs, their future dynamics are still difficult to ascertain. In addition to the inherent difficulties of this undertaking, challenges in actual assessments also depend on external shocks to the economy at large or to particular regions, along with spillover effects among neighbouring regions. PRIMA proposes to improve knowledge in scaling down this assessment. It focuses on agriculture, forestry, tourism, and ecosystem services, with special attention to the structural effects of the European policies at municipality levels. The six case studies of PRIMA, conducted in Germany, United Kingdom, France, Croatia, Czech Republic, and Bulgaria, are important for two main reasons: they provide test cases for the PRIMA approaches, and they have influenced the development of the PRIMA approaches. These case studies have been chosen for their variety of rural dynamics and governance organisation. Because of the bottom-up governance of the European cohesion policy, a large variety has been observed in the priorities and measures, targeted to several pillars of sustainable development. This variety has been narrowed in a pre-modelling stage, where 2 groups of stakeholders were interviewed: those who can assist in scenario and model development (coming from the institutions which implement policy), and the actors who may be affected by the policy and hence whose related behavioural changes should be captured by the model framework. A conceptual model has then been developed. This model focuses on the population dynamics in rural municipalities and on the decision making behaviours observed. The conceptual micro-simulation model was successfully adapted to three of the study regions (France, United Kingdom and Germany). Additionally, the developed agent-based model was adapted for the United Kingdom region; this allowed studying the effects of social aspects that are not captured in the micro-simulation model. For validation purposes, a series of workshops were conducted on the case study areas. The orientation of these workshops depended on the availability of the models for the given case study area. The workshops promoted stakeholder learning about modelling. On the whole, participants recognised models as simplifications of reality. They found explanations about the model components comprehensible, and reacted fairly favourably to the idea of having such a decision-support tool available. However, the lack of good data at a low geographical scale in most case study areas was seen as a severe limitation. Beyond pathways for model revision, some methodological advances in the field of participatory modelling have been identified. Among these is making explicit the role of a model broker, the endorsement of which should improve the various interpretations of participants. Scenario development, though far in advance of their technical skills, has also proved an efficient tool to involve stakeholders in challenging a model. Further conceptual work was identified and undertaken concerning the design of methods to reconstruct commuting network for regions where data was unavailable, to calibrate models with several number of variables and of new approaches to dynamically derive services jobs availability. PRIMA also developed a conceptual work that includes the MAGNET (formerly LEITAP) model for downscaling from world level to the country level, and a downscaling tool from country level towards the NUTS2 level. An interface has been developed for easy downscaling of scenarios. Special attention has been paid to procedures to process data from Eurostat towards a database useful as input for the downscaling model. Last, we progressed towards recommendations enhancing the scope of IA methods, with a review of literature and extensive work between all workpackages.
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@techreport{PUB00035265, author = {Turpin, N. and Hautdidier, B. and Laplana, R. and Kopeva, D. and Raley, M. and Baqueiro, O. and Deffuant, G. and Woltjer, G. and Meyer, B. and Njavro, M. and Jelinek, L. and Abrami, G. and Aznar, O. and Barreteau, O. and Bezlepkina, I. and Bouwman, A. and Franic, R. and Garrod, G. and Gomez, M. and Wander Jager, and Huet, S. and Kozáková, E. and Lenormand, M. and Marsat, J.B. and Delin, M. and Perret, E. and Rodseth, K. and Romstad, E. and ¦akic Bobic, B. and Schaft, F. and Talbot, H. and Zhang, Q.}, title = {Final Report D0.4, PRIMA collaborative project, EU 7th Framework Programme, contract no. 212345}, title = {Rapport final du projet européen PRIMA}, pages = {54}, url = {http://irsteadoc.irstea.fr/cemoa/PUB00035265 / https://prima.cemagref.fr/}, year = {2012}, affiliation = {IRSTEA CLERMONT FERRAND UMR METAFORT FRA ; IRSTEA BORDEAUX UR ADBX FRA ; IRSTEA BORDEAUX UR ADBX FRA ; UNWE SOFIA BGR ; UNEW NEWCASTLE UPON TYNE GBR ; INSTITUTE OF AGRICULTURAL DEVELOPMENT IN CENTRAL AND EASTERN DEU ; IRSTEA CLERMONT FERRAND UR LISC FRA ; WAGENINGEN UNIVERSITY NLD ; UNIVERSITY OF TECHNOLOGY DORTMUND DEU ; UNIVERSITE DE ZAGREB KRO ; UNIVERSITE DE ZAGREB KRO ; IRSTEA MONTPELLIER UR IRMO FRA ; IRSTEA CLERMONT FERRAND UMR METAFORT FRA ; IRSTEA MONTPELLIER IRMO ; LEI WAGENINGEN NLD ; - ; FACULTY OF AGRICULTURE AND TOURISM OF ZAGREB CRO ; CENTRE FOR RURAL ECONOMY SCHOOL OF AGRICULTURE, FOOD AND RURAL DEVELOPMENT NEWCASTLE UNIVERSITY GBR ; IRSTEA CLERMONT FERRAND UMR METAFORT FRA ; - ; IRSTEA CLERMONT FERRAND UR LISC FRA ; - ; IRSTEA CLERMONT FERRAND UR LISC FRA ; IRSTEA CLERMONT FERRAND UMR METAFORT FRA ; INSTITUTE OF ARGICULTURAL ECONOMICS AND INFORMATION CZR ; IRSTEA CLERMONT FERRAND UMR METAFORT FRA ; - ; UNIVERSITY OF NORWAY AAS NOR ; - ; - ; - ; -}, abstract = {Facing structural change, European rural areas still fulfil multiple social, economic and ecological functions. Because of scale interplays and sustainability trade-offs, their future dynamics are still difficult to ascertain. In addition to the inherent difficulties of this undertaking, challenges in actual assessments also depend on external shocks to the economy at large or to particular regions, along with spillover effects among neighbouring regions. PRIMA proposes to improve knowledge in scaling down this assessment. It focuses on agriculture, forestry, tourism, and ecosystem services, with special attention to the structural effects of the European policies at municipality levels. The six case studies of PRIMA, conducted in Germany, United Kingdom, France, Croatia, Czech Republic, and Bulgaria, are important for two main reasons: they provide test cases for the PRIMA approaches, and they have influenced the development of the PRIMA approaches. These case studies have been chosen for their variety of rural dynamics and governance organisation. Because of the bottom-up governance of the European cohesion policy, a large variety has been observed in the priorities and measures, targeted to several pillars of sustainable development. This variety has been narrowed in a pre-modelling stage, where 2 groups of stakeholders were interviewed: those who can assist in scenario and model development (coming from the institutions which implement policy), and the actors who may be affected by the policy and hence whose related behavioural changes should be captured by the model framework. A conceptual model has then been developed. This model focuses on the population dynamics in rural municipalities and on the decision making behaviours observed. The conceptual micro-simulation model was successfully adapted to three of the study regions (France, United Kingdom and Germany). Additionally, the developed agent-based model was adapted for the United Kingdom region; this allowed studying the effects of social aspects that are not captured in the micro-simulation model. For validation purposes, a series of workshops were conducted on the case study areas. The orientation of these workshops depended on the availability of the models for the given case study area. The workshops promoted stakeholder learning about modelling. On the whole, participants recognised models as simplifications of reality. They found explanations about the model components comprehensible, and reacted fairly favourably to the idea of having such a decision-support tool available. However, the lack of good data at a low geographical scale in most case study areas was seen as a severe limitation. Beyond pathways for model revision, some methodological advances in the field of participatory modelling have been identified. Among these is making explicit the role of a model broker, the endorsement of which should improve the various interpretations of participants. Scenario development, though far in advance of their technical skills, has also proved an efficient tool to involve stakeholders in challenging a model. Further conceptual work was identified and undertaken concerning the design of methods to reconstruct commuting network for regions where data was unavailable, to calibrate models with several number of variables and of new approaches to dynamically derive services jobs availability. PRIMA also developed a conceptual work that includes the MAGNET (formerly LEITAP) model for downscaling from world level to the country level, and a downscaling tool from country level towards the NUTS2 level. An interface has been developed for easy downscaling of scenarios. Special attention has been paid to procedures to process data from Eurostat towards a database useful as input for the downscaling model. Last, we progressed towards recommendations enhancing the scope of IA methods, with a review of literature and extensive work between all workpackages.}, }
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LISC

Lenormand Maxime

Publications

Journal Articles (6)

Book Chapters (1)

In Proceedings (7)

Miscellaneous (1)

Technical Reports (2)