Abstract: As the trial management becomes more refined,the demand of courts for accurate assessment of trial risk is gradually increasing.How to effectively carry out quantitative analysis of trial risk level is the core issue of precise risk assessment.Existing methods such as machine learning and fuzzy matrix are difficult to be effectively applied to actual trial scenes due to limited historical data and high accuracy of trial risk assessment.In response to this,this paper builds the trial risk assessment model based on the fuzzy number similarity to achieve quantitative assessment of multi-factor trial risk.This paper first establishes the multi-level risk index model based on AHP for the identification of trial risk indexes,which improves the analysis granularity and assessment objectivity of trial risk.Then,in order to obtain fuzzy risk measures,the risk aggregation model based on mixed input is constructed,which makes use of process information to improve the accuracy of assessment,and to realize the aggregation of multi-type trial risk indexes.Finally,the risk level determination model based on similarity algorithm is constructed to effectively eliminate the interference of human factors and abnormal data,and to realize the accurate measurement of multi-factor trial risk level.Based on the trial risk assessment model,this paper designs and implements the corresponding evaluation system,which includes risk calculation,risk management and risk early warning modules.Through integration and application of the corresponding evaluation system in the actual court management system,the trial risk management mode currently limited to time warning is effectively optimized,and the degree of refinement of trial management is further improved.

Key words: Fuzzy number similarity, Risk aggregation model, Risk index model, Risk level determination model, Trial risk assessment