School of Management, Shenyang University of Technology, No. 111, Shenliao West Road, Economic & Technological Development Zone, Shenyang 110870, China.
Comput Intell Neurosci. 2022 Apr 14;2022:7364375. doi: 10.1155/2022/7364375. eCollection 2022.
The judgment service rate is an important index to reflect the fairness of the judgment of legal cases in a certain area, which is of great significance to verify the accuracy of a court judgment. In this paper, a grey neural network model combining grey system theory and BP neural network algorithm is proposed to predict the index. Analyze the judgment service rate of the court judgment system, and build a prediction system based on the completion rate, completion rate, plaintiff satisfaction, defendant satisfaction, litigation time, property preservation cycle, document delivery time, implementation information disclosure rate, and other key indicators. Through example analysis, it is proved that the combined model of the grey prediction model and BP neural network has a small error and good simulation effect on the prediction of court decision-making service rate, which can better promote the development of court and society.
裁判文书上网率是反映某一地区法律案件裁判公正性的重要指标，对检验法院判决的准确性具有重要意义。本文提出了一种基于灰色系统理论和 BP 神经网络算法的灰色神经网络模型来预测该指标。对法院判决系统的裁判文书上网率进行分析，构建基于结案率、结案均衡度、原告满意度、被告满意度、诉讼时长、财产保全周期、文书送达时间、执行信息公开率等关键指标的预测系统。通过实例分析证明，灰色预测模型与 BP 神经网络的组合模型对法院裁判文书上网率的预测具有较小的误差和良好的模拟效果，能够更好地促进法院和社会的发展。
