GIS-based neural-network cellular automaton infectious-disease transmission simulation analysis method

Abstract

The invention discloses a GIS-based neural-network cellular automaton infectious-disease transmission simulation analysis method. The simulation analysis method conducts a research on an infectious-disease transmission method by comprehensively using GIS, a convolution neural network and a cellular automata and data such as infectious-disease data and investigation and statistics. Based on a geographic information system and a database technology, the simulation analysis method uses convolution neural network to mine and extract a transformation rule of the cellular automata to construct an infectious-disease transmission model, and a centralized management maintenance design mode is adopted for conducting unified control and management on infectious-disease information, cultural information and geographic information within a research area. Texts and graphics integrated functions such as maintenance and management, comprehensive inquiry, thematic maps, spatial analysis and infectious-disease transmission simulation analysis are achieved by the GIS-based neural-network cellular automaton infectious-disease transmission simulation analysis method, and the information level and auxiliary decision-making ability to deal with the infectious-disease transmission of a related department are improved.

Description

technical field [0001] The invention belongs to the technical field of data analysis, and relates to a GIS-based neural network cellular automaton infectious disease propagation simulation analysis method. Background technique [0002] The traditional cellular automaton infectious disease propagation simulation analysis method has low efficiency and cannot well meet the needs of solving problems. The present invention uses convolutional neural network to optimize the conversion rules of the cellular automata model, and applies GIS technology to it , thus improving the ability of the simulation analysis of the method. So far there is no case about the simulation analysis method of the spread of infectious diseases without GIS neural network based on cellular automata. [0003] Convolutional neural network, which avoids explicit feature sampling and implicitly learns from training data. Convolutional neural network is superior to traditional general neural network classifiers...

AI Technical Summary

Problems solved by technology

[0002] The traditional cellular automaton infectious disease propagation simulation analysis method is inefficient and cannot well meet the needs of solving problems. The present invention uses convolutional neural network to optimize the conversion rules of the cellular automata model, and applies GIS technology to it , thus improving the ability of the method to simulate and analyze

So far there is no case about the simulation analysis method of the spread of infectious diseases without GIS neural network based on cellular automata

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