A Simultaneous Calculation Method of Dynamic Simulation of Space Growth and Contribution Degree of Driving Force Factors

Abstract

The invention discloses a method for synchronously calculating the dynamic simulation of space growth and the contribution degree of the driving force factor. The invention integrates the ability of the cellular automata model (CA) to simulate the time-space evolution process of complex systems and the accurate intelligent calculation of the neural network (ANN) The advantage of land use distribution probability overcomes some inherent defects of the traditional cellular automata model in the simulation of urban land use change through the integration of advantages; the present invention improves the traditional neural network (ANN) algorithm so that it can accurately measure the importance of spatial variables It overcomes the "black box mechanism" of the traditional neural network algorithm, can accurately and transparently identify and calculate the driving force factors affecting each land use; and compared with the traditional model, it has higher precision, is suitable for multi-scale, low data requirements, and fewer parameters. , easy operation, fast speed and other practical advantages.

Description

technical field [0001] The invention relates to the technical field of geographic information science, in particular to a method and device for synchronously calculating the dynamic simulation of space growth and the contribution degree of driving force factors. Background technique [0002] The simulation of fine-grained land-use spatial growth changes has gradually attracted people's attention because it can provide detailed urban digital information to decision-makers and policy makers. Most of the previous methods focus on improving the method efficiency of urban interior simulation, but there is no mature method to explain the driving factors of the spatial growth change of fine land use. In fact, for urban planners, they are most concerned about how the internal structure of the city is formed and how they operate, so it is necessary to accurately and conveniently calculate the urban land use while performing urban land use simulation. Contribution of the driving forc...

AI Technical Summary

Problems solved by technology

Most of the previous methods focused on improving the method efficiency of urban interior simulation, but there is no mature method for how to explain the driving factors of the spatial growth change of fine land use.

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