Environmental health risk monitoring and warning system and method based on spatial Bayesian network

Abstract

The invention provides an environmental health risk monitoring and warning system and method based on a spatial Bayesian network. Spatial correlation and spatial aggregation factors are added on the basis of the traditional Bayesian network, optimized machine learning is closely combined with domain knowledge, and therefore, a network model with a more reasonable structure is generated. A spatialcorrelation / aggregation inference link is added on the basis of existing factors, and thus, the ability of Bayesian network environmental health risk monitoring and warning is enhanced. The hand-foot-mouth disease is affected by many environmental factors, which is taken as an example in the invention to explain the principle of the spatial Bayesian network and the advantage of the spatial Bayesian network in environmental health risk assessment and warning. The system and the method of the invention can be applied to the risk monitoring and warning of various diseases or health problems closely related to environmental health.

Description

technical field [0001] The invention relates to an environmental health risk monitoring and early warning system and method based on a spatial Bayesian network, and belongs to the technical field of environmental health risk monitoring and early warning. Background technique [0002] Bayesian network is a model of probability reasoning of discrete variables, which reveals the relationship between elements in the form of directed acyclic graph and joint probability distribution table between variables; compared with other methods, Bayesian network can Fusion domain knowledge and data learning for modeling, the network can integrate a variety of different types of explanatory variables to establish complex probability correlations for reasoning, and can handle missing data at the same time. The Bayesian network risk modeling method is widely used in the analysis of natural disasters and environmental health risks, and has achieved good evaluation results. However, for geospat...

AI Technical Summary

Problems solved by technology

[0003] The technical problem of the present invention is to overcome the deficiencies of the prior art, provide an environmental health risk monitoring and early warning system and method based on the spatial Bayesian network, overcome the difficulty that the traditional Bayesian network is not easy to establish spatial reasoning, and achieve improved disease prediction The goal of efficiency greatly improves the accuracy of disease identification, and solves the technical problem of low accuracy and low efficiency of disease and health risk identification functions. The present invention can identify high-risk areas more accurately, facilitating disease risk early warning and timely intervention

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