Retrieving CA nonlinear transition rule from high-dimensional feature space

Dili Xuebao/Acta Geographica Sinica

Volumn 61, Issue 6, 2006, Pages 663-672

  Liu, Xiaoping ^a   Li, Xia ^a  

^a SUN YAT SEN UNIVERSITY   (China)

Author keywords

Cellular automata; High dimensional feature space; Kernel based learning machine; Nonlinear; Transition rule

Indexed keywords

ARTIFICIAL INTELLIGENCE; CELLULAR AUTOMATON; COMPUTER SIMULATION;

ASIA; CHINA; EURASIA; FAR EAST; GUANGDONG; GUANGZHOU;

EID: 33749339781     PISSN: 03755444     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (18)

1. Batty M, Xie Y. From cells to cities. Environment and Planning B, 1994, 21: 531-548.
2. Wu Fulong. Calibration of stochastic cellular automata: the application to rural-urban land conversions. Int. J. Geographical Information Science, 2002, 16(8): 795-818.
3. White R, Engelen G. Cellular automata and fractal urban form: a cellular modelling approach to the evolution of urban land-use patterns. Environment and Planning A, 1993, 25: 1175-1199.
4. Couclelis H. From cellular automata to urban models: New principles for model development and implementation. Environment and Planning B, 1997, 24: 165-174.
5. Li Xia, Yeh A G O. Modelling sustainable urban development by the integration of constrained cellular automata and GIS. International Journal of Geographical Information Science, 2000, 14(2): 131-152.
6. Li Xia, Yeh A G O. Neural-network-based cellular automata for simulating multiple land use changes using GIS. International Journal of Geographical Information Science, 2002, 16(4): 323-343.
7. Zhou Chenghu, Sun Zhanli, Xie Yichun. Geographic Cellular Automata Study. Beijing: Science Press, 1999.
8. He Chunyang, Chen Jin, Shi Peijun et al. City expansion model of metropolitan area in China: a case study of Beijing. Acta Geographica Sinica, 2003, 58(2): 294-304.
9. Clarke K C, Hoppen S, Gaydos L. A self-modifying cellular automation model of historical urbanization in the San Francisco Bay area. Environment and Planning B: Planning and Design, 1997, 24: 247-261.
10. Fulong Wu. SimLand: a prototype to simulate land conversion through the integrated GIS and CA with AHP-derived transition rules. International Journal of Geographical Information Science, 1999, 12(1): 63-82.
11. Li Xia, Yeh A G O. Data mining of cellular automata's transition rules. International Journal of Geographical Information Science, 2004, 18(8): 723-744.
12. Mika S, Ratsch G, Weston J. Fisher discriminant analysis with kernels. Neural Networks for Signal Processing IX. New York: IEEE Press, 1999. 41-48.
13. Qingshan Liu, Hanqing Lu, Songde Ma. Improving Kernel Fisher Discriminant Analysis for face recognition. IEEE Transactions on Circuits and Systems for Video Technology, 2004, 14(1): 42-49.
14. Shen X T. Proportional odds regression and sieve maximum likelihood estimation. Biometriika, 1998, 85: 165-177.
15. Wu F, Webster C J. Simulation of land development through the integration of cellular automata and multicriteria evaluation. Environment and Planning B: Planning and Design, 1998, 25: 103-126.
16. Li Xia, Yeh A G O, Liao Qifang. Case-Based Reasoning (CBR) for land use classification using radar images. Journal of Remote Sensing, 2004, 8(3): 246-253.
17. Herbert D T, Thamas G J. Cites in space. City as Place. London: David Fulton Publishers.
18. Yan Liu, Stuart R. Modelling urban development with cellular automata incorporating fuzzy-set approaches. Computers, Environment and Urban Systems, 2003, 27: 637-658.