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Cellular automata spatial temporal data model and forecasting approach
Authors:REN Hai jun  ZHANG Xiao xing and ZHOU Quan
Institution:State Key Laboratory of Power Transmission Equipment & System Security and New Technology ;College of Software Engineering ,Chongqing University,Chongqing 400044,P.R. China;State Key Laboratory of Power Transmission Equipment & System Security and New Technology,Chongqing University,Chongqing 400044,P.R. China;State Key Laboratory of Power Transmission Equipment & System Security and New Technology,Chongqing University,Chongqing 400044,P.R. China
Abstract:The standard cellular automata(CA) model is expanded to meet requests of space time dynamic simulation and forecast under the platform of geographic information system(GIS). Taking power load forecasting of the electric power industry as the specific application, the relations between dynamic model of the land use and power load space are established. The data and attribute data interactive discrete in spatial temporal data management have been solved. The CA theory is practically used to simulate the process of urban land use dynamic development, to forecast future land use types of each small area, to establish spatial load forecasting model. It breaks through the localization of all kinds of forecasting methods of traditional space time separation power prediction. The effectiveness of the prediction method is verified by example.
Keywords:cellular automata  spatial temporal data model  land use decision making  electric load forecasting
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