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http://dx.doi.org/10.11108/kagis.2010.13.3.119

An Application of the Genetic Algorithm on Population Estimation Using Urban Environmental Factors  

Choei, Nae-Young (Department of Urban Engineering, Hongik University)
Publication Information
Journal of the Korean Association of Geographic Information Studies / v.13, no.3, 2010 , pp. 119-130 More about this Journal
Abstract
The Genetic Algorithm has been frequently applied by many researchers as one of the population surface modelling tool in estimating the regional population based on the gridded spatial system. Taking the East-Hwasung area as the case, this study first builds a gridded population data based on the KLIS and eAIS databases as well as municipal population survey data, and then constructs the attribute values of the explanatory variables by way of GIS tools. The GA model is run to maximize its fitness function measuring the correlation coefficient between the observed and predicted values of the 70 population cells. It is shown that the GA output predicted reasonably consistent and meaningful coefficient estimates for the explanatory variables of the model.
Keywords
Genetic Algorithm; Population Estimation; Urban Environment; KLIS; eAIS;
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Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
1 국토해양부. 2008a. 기반시설부담구역제도 시행 및 운영활성화를 위한 연구.
2 국토해양부. 2008b. 기반시설부담구역제도 운영편람.
3 김형복, 전병은, 최내영. 2007. 기반시설부담금에 관한 법률 및 그 운영에 대한 특강자료. 대한국토.도시계획학회 국토도시아카데미.
4 최내영. 2009. 인구증가 분석격자의 공간정보를 이용한 기반시설 부담구역 설정방안. 한국지리정보학회지 12(4): 74-83.
5 화성시. 2004. 화성시 기반시설부담구역 지정 및 부담계획 기준수립 연구.
6 Anselin, L., N. Lozano and J. Koschinsky. 2006. Rate transformations and smoothing. A discussion paper of the Spatial Analysis Laboratory, University of Illinois at Urbana-Champaign.
7 Balakrishnan, P.V. and V.S. Jacob. 1996. Genetic algorithms for product design, Management Science 42(8):1105-1117.   DOI   ScienceOn
8 Holland, H.H. 1975. Adaptation in Natural and Artificial Systems. The University of Michigan Press: Ann Arbor.
9 Koza, J.R. 1990. Genetic Programming: A Paradigm for Genetically Breeding Populations of Computer Programs to Solve Problems, Stanford University Report, Report No. STAN-CS-90-1394.
10 Li, X. and A.G. Yeh. 2005. Integration of genetic algorithms and GIS for optimal location search. International Journal of Geographical Information Science 19(5) :581-601.   DOI   ScienceOn
11 Manson, S.M. 2005. Agent-based modeling and genetic programming for modeling land change in the Southern Yucatan Peninsular Region of Mexico. Agriculture, Ecosystems and Environment 111:47- 62.   DOI   ScienceOn
12 Muttil, N and J. Lee. 2005. Genetic programming for analysis and real-time prediction of coastal algal blooms. Ecological Modelling 189:363-376.   DOI   ScienceOn
13 Yue, T.X., Y.A. Wang, S.P. Chen, J.Y. Liu, D.S. Qiu, X.Z. Deng, M.L. Liu and Y.Z. Tian. 2003. Numerical simulation of population distribution in China. Population and Environment 25(2):141- 163.
14 Yue, T.X., Z.P. Du and Y.J. Song. 2008. Spatial models and geographic information systems. Encyclopedia of Ecology, 3315-3325.   DOI