Improved CA-Markov Model for Predicting Evolution of Urban Land Spatial Structure
The prediction for urban land spatial structure evolution requires a large amount of data.Currently,some prediction methods only have low prediction accuracy.Therefore,a prediction method for urban land spatial structure evolution was proposed.Firstly,urban land spatial structure data was obtained by GIS technology,and then its structural evolution was analyzed.Moreover,the CA model was optimized through an artificial neural network mod-el,roulette competition mechanism,and inertia coefficient.Meanwhile,the improved CA model was combined with Markov structure to construct an improved CA Markov model.Based on the analysis result,the evolution of urban land spatial structure was predicted.Experimental results show that the proposed method has higher accuracy in predicting the evolution of urban land spatial structure and better overall application effect.
Urban land spatial structureEvolution predictionGIS technologyCA-MarkovOptimization of CA model