Abstract
The emphasis on calibration method of neural network (NN) based cellular automata (CA) models has been limited to back propagation (BP) mostly and not much work has been done to study the effect of different NN training methods. In this article the dynamic annealing (DA) method for training NN has been compared with BP. Also the effect of various neighborhood sizes for CA has been analyzed in the context of dynamic spatial modeling for urban growth. The model has been implemented and verified for Thane city, Maharashtra state, India as this city has higher rate of urbanization compared to other cities in the state. © 2009 Springer Berlin Heidelberg.
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CITATION STYLE
Mahajan, Y., & Venkatachalam, P. (2009). Neural network based cellular automata model for dynamic spatial modeling in GIS. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5592 LNCS, pp. 341–352). https://doi.org/10.1007/978-3-642-02454-2_24
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