参考文献
[1]邓建锋.基于R语言的罪犯数据聚类研究[D].广州:中山大学,2014.
[2]赵军.我国犯罪预测及其研究的现状、问题与发展趋势——对“中国知网”的内容分析[J].湖南大学学报(社会科学版),2011,25(3):155-160.
[3]李明,薛安荣,王富强,等.犯罪量动态优化组合预测方法[J].计算机工程,2011,37(17):274-275.
[4]孙菲菲,曹卓,肖晓雷.基于随机森林的分类器在犯罪预测中的应用研究[J].情报杂志,2014(10):148-152.
[5]罗森林,刘峥,郭亮,等.基于Probit的犯罪嫌疑人判定方法研究[J].北京理工大学学报,2011,31(11):1337-1341.
[6]XIANG Yang,CHAU M,ATABAKHSH H,et al.Visualizing Criminal Relationships:Comparison of a Hyperbolic Tree and a Hierarchical List[J].Decision Support Systems,2005,41(1):69-83.
[7]BRUNSDON C,CORCORAN J,HIGGS G.Visualising Space and Time in Crime Patterns:A Comparison of Methods[J].Computers Environment & Urban Systems,2007,31(1):52-75.
[8]ENZMANN D,PODANA Z.Official Crime Statistics and Survey Data:Comparing Trends of Youth Violence Between 2000 and 2006 in Cities of the Czech Republic,Germany,Poland,Russia,and Slovenia[J].European Journal on Criminal Policy & Research,2010,16(3):191-205.
[9]TOLLENAAR N,HEIJDEN P G M V D.Which Method Predicts Recidivism Best?:A Comparison of Statistical,Machine Learning and Data Mining Predictive Models[J].Journal of the Royal Statistical Society,2013,176(2):565-584.
[10]USHA D,RAMESHKUMAR K.A Complete Survey on Application of Frequent Pattern Mining and Association Rule Mining on Crime Pattern Mining[J].International Journal of Advances in Computer Science and Technology,2014,3(4):264-275.
[11]AYAT S,FARAHANI H A,AGHAMOHAMADI M,et al.A Comparison of Artificial Neural Networks Learning Algorithms in Predicting Tendency for Suicide[J].Neural Computing & Applications,2013,23(5):1381-1386.
[12]PFLUEGER M O,FRANKE I,GRAF M,et al.Predicting General Criminal Recidivism in Mentally Disordered Offenders Using a Random Forest Approach[J].BMC Psychiatry,2015,15(1):1-10.
[13]VURAL M S,GOK M.Criminal Prediction Using Naive Bayes Theory[J].Neural Computing & Applications,2016:1-12.
[14]罗瑜.支持向量机在机器学习中的应用研究[D].成都:西南交通大学,2007.
[15]闫志勇,关欣,李锵.基于SVM和增强型PCP特征的和弦识别[J].计算机工程,2014,40(7):170-173.
[16]安欣,徐硕,张录达,等.多因变量LS-SVM回归算法及其在近红外光谱定量分析中的应用[J].光谱学与光谱分析,2009,29(1):127-130.
[17]丁芳.基于Rijke管的热声振动涡脱落现象研究及SVM时间序列预测模型[D].杭州:浙江大学,2016.
[18]TRELEA I C.The Particle Swarm Optimization Algorithm:Convergence Analysis and Parameter Selection[J].Information Processing Letters,2003,85(6):317-325.
[19]郑伟,吕建新,马艳丽.一种基于扩展互信息算法的特征选择方法[J].微计算机信息,2010,26(24):223-224.
[20]HSU C W,LIN C J.A Comparison of Methods for Multiclass Support Vector Machines[J].IEEE Transactions on Neural Networks,2002,13(2):415-425.
编辑刘冰 |