Cellular automata spatialtemporal data model and forecasting approach
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Abstract:
The standard cellular automata(CA) model is expanded to meet requests of spacetime 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 spatialtemporal data management have been solved. The CA theory is practically used to simulate the process of urban landuse dynamic development, to forecast future landuse types of each smallarea, to establish spatial load forecasting model. It breaks through the localization of all kinds of forecasting methods of traditional spacetime separation power prediction. The effectiveness of the prediction method is verified by example.
