A New Adaptive Prediction Algorithm for Judicial Sentencing with Empirical Studies  

作　　者：DAI Ruifen WANG Fang GUO Lei 

机构地区：[1]Data Science Institute,Shandong University,Jinan,250100,China [2]Key Laboratory of Systems and Control,Academy of Mathematics and Systems Science,Chinese Academy of Sciences,Beijing,100190,China

出　　处：《Journal of Systems Science & Complexity》2025年第1期3-20,共18页系统科学与复杂性学报(英文版)

基　　金：supported by the National Natural Science Foundation of China under Grant Nos.T2293773,72371145,and 12288201;the Special Funds for Taishan Scholars Project of Shandong Province,China under Grant No.tsqn202211004;National Key Research and Development Program under Grant No.2022YFC3303000.

摘　　要：With the development and applications of the Smart Court System(SCS)in China,the reliability and accuracy of legal artificial intelligence have become focal points in recent years.Notably,criminal sentencing prediction,a significant component of the SCS,has also garnered widespread attention.According to the Chinese criminal law,actual sentencing data exhibits a saturated property due to statutory penalty ranges,but this mechanism has been ignored by most existing studies.Given this,the authors propose a sentencing prediction model that combines judicial sentencing mechanisms including saturated outputs and floating boundaries with neural networks.Building on the saturated structure of our model,a more effective adaptive prediction algorithm will be constructed based on the fusion of several key ideas and techniques that include the utilization of the L1 loss together with the corresponding gradient update strategy,a data pre-processing method based on large language model to extract semantically complex sentencing elements using prior legal knowledge,the choice of appropriate initial conditions for the learning algorithm and the construction of a double-hidden-layer network structure.An empirical study on the crime of disguising or concealing proceeds of crime demonstrates that our method can achieve superior sentencing prediction accuracy and significantly outperform common baseline methods.

关 键 词：Adaptive prediction algorithm judicial mechanism neural networks sentencing prediction 

分 类 号：TP391[自动化与计算机技术—计算机应用技术] TP18[自动化与计算机技术—计算机科学与技术]