计算机科学 ›› 2021, Vol. 48 ›› Issue (5): 209-216.doi: 10.11896/jsjkx.200500034

• 人工智能 • 上一篇    下一篇

基于模糊数相似度的审判风险评估系统

雍琪1, 蒋维娜1, 罗育泽2   

  1. 1 中山大学数据科学与计算机学院 广州511400
    2 中山大学国家数字家庭工程技术研究中心 广州511400
  • 收稿日期:2020-05-11 修回日期:2020-08-08 出版日期:2021-05-15 发布日期:2021-05-09
  • 通讯作者: 罗育泽(yzluo26@126.com)
  • 基金资助:
    国家重点研发计划项目(2018YFC0830500)

Trial Risk Assessment System Based on Fuzzy Number Similarity

YONG Qi1, JIANG Wei-na1, LUO Yu-ze2   

  1. 1 School of Data and Computer Science,Sun Yat-sen University,Guangzhou 511400,China
    2 National Engineering Research Center of Digital Life,Sun Yat-sen University,Guangzhou 511400,China
  • Received:2020-05-11 Revised:2020-08-08 Online:2021-05-15 Published:2021-05-09
  • About author:YONG Qi,born in 1996,postgraduate.Her main research interests include fuzzy set theory and risk analysis.(yongq@mail2.sysu.edu.cn)
    LUO Yu-ze,born in 1987,bachelor.His main research interests include fuzzy set theory and risk analysis.
  • Supported by:
    National Key Research and Development Plan of China(2018YFC0830500).

摘要: 随着审判管理日趋精细化,法院对审判风险精准化评估的需求逐渐增多,其中,如何有效进行审判风险等级定量分析是精准化风险评估的核心问题。现有的机器学习、风险矩阵等方法由于存在历史数据有限、审判风险评估精度要求高等不足,难以有效地应用于实际审判业务中。针对此问题,构建了基于模糊数相似度的审判风险评估模型,实现了多因素审判风险的定量评估。首先针对审判风险指标进行辨识,建立了基于AHP的多层级风险指标模型,以提升审判风险的分析粒度和评价客观性;然后,为了获取模糊风险测度,设计了基于混合输入的风险聚合模型,该模型应用流程信息来提高评估准确性,实现了审判风险指标的分类聚合;最后,构建了基于相似度算法的风险等级确定模型,该模型能够有效排除人为因素和异常数据的干扰,实现了审判风险等级的精准度量。基于审判风险评估模型,设计并实现了相应的评估系统,该评估系统包括风险计算、风险管理和风险预警模块,通过在实际法院管理系统中进行集成和应用,该评估系统有效优化了目前局限于审限预警的审判风险管理模式,进一步提高了审判管理的精细化程度。

关键词: 风险等级确定模型, 风险聚合模型, 风险指标模型, 模糊数相似度, 审判风险评估

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

中图分类号: 

  • TP315
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