Deep learning cellular automaton simulation analysis method based on geographic information system

A geographic information system and cellular automata technology, applied in the field of data simulation, can solve problems such as problems to be improved, and achieve the effect of rapid analysis and evaluation

Inactive Publication Date: 2015-08-19
WUHAN UNIV
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Problems solved by technology

[0004] Compared with neural network, deep learning shows better ability to solve problems. Currently, there are simulation analysis methods for neural network optimization of cellular automata, but the ability to solve problems needs to be improved.

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  • Deep learning cellular automaton simulation analysis method based on geographic information system
  • Deep learning cellular automaton simulation analysis method based on geographic information system
  • Deep learning cellular automaton simulation analysis method based on geographic information system

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Embodiment Construction

[0035] The present invention will be described in detail below in combination with specific embodiments.

[0036] The step process of the present invention is as Figure 1 to Figure 5 As shown, the first is to build a simulation analysis database, which mainly includes a spatial database and an attribute database. The database can be a database for certain applications, such as river bed evolution prediction, flood disaster simulation, and infectious disease spread. This invention applies deep learning To mine and extract the transformation rules of cellular automata, and then use the cellular automata to learn the prepared simulation analysis data, and apply the geographic information system to this field, so as to build a deep learning element based on geographic information system Cellular automata simulation analysis method. The concrete implementation steps of this invention are as follows:

[0037] 1. Obtain geographic information, including spatial data and attribute ...

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Abstract

The invention discloses a deep learning cellular automaton simulation analysis method based on a geographic information system. Comprehensive simulation analysis is performed on data through comprehensive use of the geographic information system, deep learning, a cellular automaton and the like. The method is based on the technologies of geographic information system, database and the like; the conversion rule of the cellular automaton is mined and extracted through deep learning, and a model is built; and the design mode of centralized management and maintenance is adopted for performing unified control and management on information in a research region. The functions of illustrated integrated maintenance management, comprehensive inquiry, spatial analysis and simulation analysis are realized. The method has the beneficial effects that a method and technology of simulation analysis are researched through comprehensive use of the geographic information system, deep learning, the cellular automaton and a spatial analysis technology, and innovation is realized on a theoretical method in the field.

Description

technical field [0001] The invention belongs to the technical field of data simulation, and relates to a deep learning cellular automaton simulation analysis method based on a geographic information system. Background technique [0002] Nowadays, deep learning has become a popular field of big data and artificial intelligence. By establishing a layered model structure similar to the human brain, this method extracts the features from the bottom to the top of the input data step by step, so that it can well establish a model from the bottom to the top. High-level mapping relationship. Deep learning methods can achieve complex function approximation by learning a deep nonlinear network structure, characterize the distributed representation of input data, and demonstrate a powerful ability to learn the essential characteristics of data sets from a small number of sample sets. [0003] The geographic information system is a spatial information analysis and simulation system, wh...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/50G06N3/10
Inventor 董文永董学士刘宇航王豫峰康岚兰
Owner WUHAN UNIV
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