Reliable consumable risk assessment method based on Bayes reinforcement learning

Abstract

The present invention provides a reliable consumable risk assessment method based on Bayes reinforcement learning which solves the key information of consumable safety and provides data basis for design and recalling of consumables so as to guarantee the customer safety and market stabilization. The method performs historical data processing and screening, defines and establish a 'customer-product-environment' multi-type and multi-layer risk factor feature model, a damaging factor relation model and a Bayesian network topology structure, and establishes a condition probability table to calculate a particular commodity damaging event generation probability based on the election EM algorithm to realize prediction of damaging event generation, obtain the posterior probability when some types of damaging event are generated and finally five out multi-dimensional information output comprising the maximum risk grade and a task factor association relation so as to provide rich data basis for risk elimination of a consumable design phase.

Description

technical field [0001] The invention relates to the technical field of consumer product safety, in particular to a reliable consumer product risk assessment method based on Bayes enhanced learning. Background technique [0002] With the continuous development of the economy and society, a large number of applications of new materials and new processes, a wide variety and large quantities of consumer goods have flooded into the market; many injury incidents from children's toys, accessories to clothing, household appliances and other consumer goods have made consumers' health The serious threat has also had a huge negative impact on the international competitiveness and credibility of my country's consumer goods. The elimination of safety risks of consumer products has become an urgent problem to be solved. [0003] The key link that causes frequent consumer product safety problems is the design link; consumer product risk assessment technology can provide prior knowledge for...

AI Technical Summary

Problems solved by technology

[0006] To sum up, the existing risk assessment does not fully take into account multiple factors of consumer-product-environment, and cannot analyze the possible changes of other related factors caused by the random changes of some risk factors, and the accuracy of inferring the category of injury is low.

It is difficult to meet the design-time risk assessment requirements of consumer product manufacturers, and it is also difficult to provide a basis for consumer product recalls

The actual security needs urgently require an innovative development of a reliable consumer product evaluation method on the basis of in-depth analysis of the coupling relationship between consumer risk factors, so as to realize the analysis of the risk level of consumer products and solve the problems of low efficiency and poor universality of current consumer product evaluation.

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