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Data Analysis and Knowledge Discovery  2019, Vol. 3 Issue (11): 70-78    DOI: 10.11925/infotech.2096-3467.2019.0422
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Risk Assessment System for Prisons Based on Interval-valued Fuzzy VIKOR Method
Yang Shen1(),Weichao Zhuang1,Qinghua Wu2,Lingfei Qian1
1 College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing 210006, China
2 Wuxi Zhuoxin Information Technology Co., Ltd, Wuxi 214000, China
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Abstract  

[Objective] This study tries to improve the assessment of prison risks, such as violence, suicide, being abetting or abetted. [Methods] We proposed a risk assessment system for prisoners based on the interval-valued fuzzy VIKOR method. First, on the basis of 62-dimesion sample data of more than 1100 prisoner records, we established the optimized data set with interval-valued fuzzy VIKOR method. Then, we trained the new model with multiple machine learning algorithms. Finally, we compared the performance of our model with the existing ones. [Results] The precision, recall and F1 values were improved by 8.9%, 11.1% and 0.1 respectively. [Limitations] We could not propose a universal algorithm for all types of risks. [Conclusions] Our model provides some new directions for prison management and research.

Key wordsPrisoner      Characteristics      Risk      Assessment      the      Interval-Valued      Fuzzy      VIKOR      Machine      Learning     
Received: 22 April 2019      Published: 18 December 2019
ZTFLH:  TP393  
Corresponding Authors: Yang Shen     E-mail: shen.y@nuaa.edu.cn

Cite this article:

Yang Shen,Weichao Zhuang,Qinghua Wu,Lingfei Qian. Risk Assessment System for Prisons Based on Interval-valued Fuzzy VIKOR Method. Data Analysis and Knowledge Discovery, 2019, 3(11): 70-78.

URL:

http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.2096-3467.2019.0422     OR     http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2019/V3/I11/70

比较项 暴力型监犯 心理问题型监犯 教唆他人型监犯 缺乏辨识型监犯
性格特征 脾气暴躁 心理压力大 善于观察利用他人 文化素质低、缺乏辨识能力
犯罪类型特征 故意杀人、抢劫罪、故意
伤害罪等
强奸、猥亵儿童等 经济型犯罪、诈骗罪、煽动
民族仇恨罪等
窝藏罪、包庇罪、参加极端主
义等
风险类型 监狱暴力 恶意报复、自杀 教唆他人有组织地违法乱纪 参加他人教唆的乱纪活动
一类特征 二类特征
刑期 刑期1-3年
刑期3-5年
刑期5-10年
刑期10-20年
犯罪类型 暴力型犯罪
心理问题型犯罪
教唆他人型犯罪
缺乏辨识型犯罪
职业 从事职业数量
家庭情况 亲属数量
团伙 是否团伙作案
地区 北疆地区
南疆地区
东疆地区
外省地区
婚姻情况 是否已婚
监犯编号 评价专家
编号
暴力倾向
下限
暴力倾向
上限
心理问题
倾向下限
心理问题
倾向上限
教唆他人
倾向下限
教唆他人
倾向上限
缺乏辨识
倾向下限
缺乏辨识
倾向上限
6520015418 1 0.10 0.20 0.25 0.35 0.35 0.45 0.10 0.20
2 0.15 0.25 0.30 0.40 0.40 0.45 0.15 0.25
3 0.10 0.15 0.25 0.40 0.30 0.40 0.05 0.25
4 0.10 0.25 0.25 0.35 0.25 0.45 0.20 0.30
监犯编号 暴力倾向 心理问题倾向 教唆他人倾向 缺乏辨识倾向
6520015418 0.20 0.35 0.43 0.21
机器学习算法 拟合优度R2 关键参数值
神经网络 0.12 activation='relu'
随机森林 0.76 n_estimators=50, max_depth=8
决策树 0.86 random_state=2, max_depth=10
SVM 0.45 C=1
KNN 0.44 n_neighbors=9
XGBoost 0.48 n_estimators=25
监犯编号 暴力型 心理问题型 教唆他人型 缺乏辨识型 平均值
6520017131 0.38 0.06 0.00 0.00 0.11
6520015387 0.62 0.20 0.12 0.14 0.27
6520016620 0.62 0.35 0.12 0.14 0.31
6520007860 0.22 0.25 0.82 0.31 0.40
6520006994 0.58 0.01 0.00 0.07 0.16
监犯犯事 监犯未犯事
预测监犯犯事 161 69
预测监犯未犯事 73 357
监犯犯事 监犯未犯事
预测监犯犯事 187 50
预测监犯未犯事 47 376
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