Data/hora: 14/05/2024 02:43:00

Biblioteca(s): | Embrapa Agricultura Digital.
Data corrente: | 13/10/2010
Data da última atualização: | 05/11/2010
Autoria: | GARGIULO, F.; TERNES, S.; HUET, S.; DEFFUANT, G.
Afiliação: | FLORIANA GARGIULO, LISC/CEMAGREF; SONIA TERNES, CNPTIA, LISC/CEMAGREF; SYLVIE HUET, LISC/CEMAGREF; GUILLAUME DEFFUANT, LISC/CEMAGREF.
Título: | An iterative approach for generating statistically realistic populations of households.
Ano de publicação: | 2010
Fonte/Imprenta: | PLoS ONE, San Francisco, v. 5, n. 1, 2010.
Páginas: | p. 1-9.
DOI: | 10.1371/journal.pone.0008828.t002
Idioma: | Inglês
Conteúdo: | Background. Many different simulation frameworks, in different topics, need to treat realistic datasets to initialize and calibrate the system. A precise reproduction of initial states is extremely important to obtain reliable forecast from the model. Methodology/Principal Findings. This paper proposes an algorithm to create an artificial population where individuals are described by their age, and are gathered in households respecting a variety of statistical constraints (distribution of household types, sizes, age of household head, difference of age between partners and among parents and children). Such a population is often the initial state of microsimulation or (agent) individual-based models. To get a realistic distribution of households is often very important, because this distribution has an impact on the demographic evolution. Usual techniques from microsimulation approach cross different sources of aggregated data for generating individuals. In our case the number of combinations of different households (types, sizes, age of participants) makes it computationally difficult to use directly such methods. Hence we developed a specific algorithm to make the problem more easily tractable. Conclusions/Significance. We generate the populations of two pilot municipalities in Auvergne region (France) to illustrate the approach. The generated populations show a good agreement with the available statistical datasets (not used for the generation) and are obtained in a reasonable computational time.
Palavras-Chave: | Algorithm; Algoritmo; Artificial population; População x tarefas do lar; Population distributed in households; Projeto PRIMA; Prototypical Policy Impacts on Multifunctional Activities - PRIMA; Simulation; Synthetic population.
Thesagro: | Simulação.
Categoria do assunto: | --
URL: | http://ainfo.cnptia.embrapa.br/digital/bitstream/item/23288/1/journal.pone.0008828.pdf
Registro original: | Embrapa Agricultura Digital (CNPTIA)
Exemplares: | CNPTIA - (15168-1) - UPC - AP - DD -  -  -  - DIS