[1] 吉根林, 赵斌. 面向大数据的时空数据挖掘综述[J]. 南京师大学报(自然科学版), 2014, 37(1):1-7. Jin Genlin, Zhao Bin. A Review of spatio-temporal data mining for big data[J]. Journal of Nanjing Normal University (Science & Technology Edition), 2014, 37(1):1-7
[2] 王刚, 黄丽华, 张成洪, 等. 数据挖掘分类算法研究综述[J]. 科技导报, 2006, 24(12):73-76. Wang Gang, Huang Lihua, Zhang Chenghong, et al. Research summary of data mining classification algorithm[J]. Science Technology Review, 2006, 24(12):73-76.
[3] 李海林, 梁叶, 王少春. 时间序列数据挖掘中的动态时间弯曲研究综述[J]. 控制与决策, 2017, doi:10.13195/j.kzyjc.2017. 1037. Li Hailin, Liang Ye, Wang Shaochun. Review of dynamic time bending in time series data mining[J]. Control and Decision Making, 2017, doi:10.13195/j.kzyjc.2017.1037.
[4] 龚著琳, 陈瑛, 苏懿, 等. 数据挖掘在生物医学数据分析中的应用[J]. 上海交通大学学报(医学版), 2010, 30(11):1420-1423. Gong Zhulin, Chen Ying, Su Yi, et al. Application of data mining in biomedical data analysis[J]. Journal of Shanghai Jiaotong University(Medical Science), 2010, 30(11):1420-1423.
[5] 屈芳, 郭骅."互联网+大数据"养老的实现路径[J]. 科技导报, 2017, 35(16):84-90. Qu Fang, Guo Hua. "Internet + big data" pension path to achieve[J]. Science & Technology Review, 2017, 35(16):84-90.
[6] Pan T L, Sumalee A, Zhong R X, et al. Short-term traffic state prediction based on temporal-spatial correlation[J]. IEEE Transactions on Intelligent Transportation Systems, 2013, 14(3):1242-1254.
[7] Wright J, Yang A Y, Ganesh A, et al. Robust face recognition via sparse representation[J]. IEEE Transactions on Pattern Analysis & Machine Intelligence, 2008, 31(2):210-227.
[8] 沙亚清, 孙宏伟, 顾明. 基于智能卡和指纹识别的电子报税认证系统[J]. 计算机工程, 2006, 32(14):133-135. Sha Yaqing, Sun Hongwei, Gu Ming, et al. Electronic tax certification system based on smart card and fingerprint identification[J]. Computer Engineering, 2006, 32(14):133-135.
[9] 周磊, 武建军, 张洁. 以遥感为基础的干旱监测方法研究进展[J]. 地理科学, 2015, 35(5):630-636. Zhou Lei, Wu Jianjun, Zhang Jie. Research progress of remote sensing based drought monitoring methods[J]. Geography Science, 2015, 35(5):630-636.
[10] 谢玮, 刘斌, 刘鑫,等. 大数据时代的石油地震勘探系统与软件平台[J]. 科技导报, 2017, 35(15):57-62. Xie Wei, Liu Bin, Liu Xin, et al. Petroleum seismic exploration system and software platform in big data era[J]. Science & Technology Review, 2017, 35(29):172-174.
[11] Bishop C M. Neural networks for pattern recognition[M]. New York:Oxford University Press, 1995.
[12] Kistler, Werner M. Spiking neuron models[M]. Cambridge:Cambridge University Press, 2002.
[13] Lécun Y, Bottou L, Bengio Y, et al. Gradient-based learning applied to document recognition[J]. Proceedings of the IEEE, 1998, 86(11):2278-2324.
[14] Quinlan J R. C4.5:Programs for machine learning[M]. Cambridge:Morgan Kaufmann Publishers Inc., 1992.
[15] 万赟. 从图灵测试到深度学习:人工智能60年[J]. 科技导报, 2016, 34(7):26-33. Wan Yun. From Turing test to in-depth learning:60 years of artificial intelligence[J]. Science & Technology Review, 2016, 34(7):26-33.
[16] Quinlan J R. Introduction of decision trees[J]. Machine Learning, 1986(1):81-106.
[17] Guo H, Gelfand S B. Classification trees with neural network feature extraction[J]. IEEE Transactions on Neural Networks, 1992, 3(6):923-33.
[18] 何禹德. 基于数据挖掘技术的糖尿病临床数据分析[D]. 长春:长春工业大学, 2016. He Yude. Clinical data analysis of diabetes based on data mining technology[D]. Changchun:Changchun University of Technology, 2016.
[19] Li W, Han J, Pei J. CMAR:Accurate and efficient classification based on multiple class-association rules[C]//Proceedings 2001 IEEE International Conference on Data Mining. Piscataway NJ:IEEE, 2001, 28(6):369-376.
[20] Han J, Yin X. CPAR:Classification based on predictive association rules[J]. Lecture Notes of the Institute for Computer Sciences Social Informatics & Telecommunications Engineering, 2003, 24:236-255.
[21] 唐晓东. 基于关联规则映射的生物信息网络多维数据挖掘算法[J]. 计算机应用研究, 2015, 32(6):1614-1616. Tang Xiaodong. Multidimensional data mining algorithm for bioinformatics network based on association rule mapping[J]. Application Research of Computers, 2015, 32(6):1614-1616.
[22] Liu B, Hsu W, Ma Y. Integrating classification and association rule mining[C]//Proceedings of the 4th International Conference on Knowledge Discovery and Data Mining California AAAI, 1998, 1711:80-86.
[23] Bishop C M. Pattern recognition and machine learning (Information science and statistics)[M]. New York:Springer-Verlag New York, Inc., 2006.
[24] Friedman N, Dan G, Goldszmidt M. Bayesian network classifiers[J]. Machine Learning, 1997, 29(2/3):131-163.
[25] Sahami M. Learning limited dependence Bayesian classifiers[C]//International Conference of Knowledge Discovery and Data Mining. California:AAAI,1996:335-338.
[26] 朱凌云, 吴宝明. 医学数据挖掘的技术、方法及应用[J]. 生物医学工程学杂志, 2003(3):559-562. Zhu Lingyun, Wu Baoming. Techniques, methods and applications of medical data mining[J]. Biomedical Engineering Journal, 2003(3):559-562.
[27] Holland J H. Adaptation in natural and artificial systems:An introductory analysis with applications to biology, control, and artificial intelligence[M]. Cambridge:The MIT Press, 1975.
[28] Eberhart R, Kennedy J. A new optimizer using particle swarm theory[C]//Proceedings of the Sixth International Symposium on International Symposium on MICRO Machine and Human Science, 1995. Piscataway NJ:IEEE, 2002:39-43.
[29] 邓乃扬, 田英杰. 支持向量机:理论、算法与拓展[M]. 北京:科学出版社, 2009. Deng Naiyang, Tian Yingjie. Support vector machines:Theory, algorithms, and extensions[M]. Beijing:Science Press, 2009.
[30] Drucker H, Burges C J C, Kaufman L, et al. Support vector regression machines[J]. Advances in Neural Information Processing Systems, 1996, 28(7):779-784.
[31] Hsieh C J, Chang K W, Lin C J, et al. A dual coordinate descent method for large-scale linear SVM[C]//Proceeding of International Conference on Machine Learning. New York:ACM, 2008:408-415.
[32] 肖娟. 数据挖掘在物流业的应用综述[J]. 统计与决策, 2013(11):95-97. Xiao Juan. Application of data mining in logistics industry[J]. Statistics and Decision, 2013(11):95-97.
[33] Chen Y C, Chen C C, Peng W C, et al. Mining correlation patterns among appliances in smart home environment[J]. Lecture Notes in Computer Science, 2014, 8444:222-233..
[34] Ollmann G. The evolution of commercial malware development kits and colour-by-numberscustom malware[J]. Computer Fraud & Security, 2008(9):4-7.
[35] Ghiasi M, Sami A, Salehi Z. Dynamic VSA:A framework for malware detection based on register contents[J]. Engineering Applications of Artificial Intelligence, 2015, 44:111-122.
[36] Bruschi D, Martignoni L, Monga M. Detecting self-mutating malware using control-flow graph matching[C]//International Conference on Detection of Intrusions and Malware & Vulnerability Assessment. Verlag:Springer-Verlag, 2006:129-143.
[37] Kuzurin N, Shokurov A, Varnovsky N, et al. On the concept of software obfuscation in computer security[C]//International Conference on Information Security. Verlag:Springer-Verlag, 2007:281-298.
[38] Christodorescu M, Jha S. Testing malware detectors[C]//ACM Sigsoft International Symposium on Software Testing and Analysis. New York:ACM, 2004:34-44.
[39] Norouzi M, Souri A, Zamini M S. A data mining classification approach for behavioral malware detection[M]. Cairo:Hindawi Publishing Corp., 2016.
[40] 孙勤红. 基于梯度采样局部收敛的生物信息大数据挖掘[J]. 科技通报, 2015, 31(10):214-216. Sun Qinhong. Bioinformatics big data mining based on gradient sample local convergence[J]. Bulletin of Science and Technology, 2015, 31(10):214-216.
[41] 朱佳俊, 郑建国, 李金兵. 基于粗糙分类的不确定可拓群决策数据挖掘及应用[J]. 控制与决策, 2012, 27(6):850-854. Zhu Jiajun, Zheng Jianguo, Li Jinbing. Uncertain extension computer aided decision data mining based on rough classification[J]. Control and Decision Making, 2012, 27(6):850-854.
[42] Chen L H, Chiou T W. A fuzzy credit-rating approach for commercial loans:A Taiwan case[J]. Omega, 1999, 27(4):407-419.
[43] 刘铭, 张双全, 何禹德. 基于改进型模糊神经网络的信用卡客户违约预测[J]. 模糊系统与数学, 2017(1):143-148. Liu Ming, Zhang Shuangquan, He Yude. Credit card customer default prediction based on improved fuzzy neural network[J]. Fuzzy Systems and Mathematics, 2017(1):143-148.
[44] Fernandes K, Cardoso J S, Fernandes J. Transfer learning with partial observability applied to cervical cancer screening[C]//Iberian Conference on Pattern Recognition and Image Analysis. Berlin:Springer, 2017:243-250.
[45] Mangasarian O L, Street W N, Wolberg W H. Breast cancer diagnosis and prognosis via linear programming[J]. Operations Research, 1995, 43(4):570-577.
[46] Liu M, Dong X G. The application of improved BP neural network in the diagnosis of breast tumors[C]//International Conference on Systems and Informatics. Piscataway NJ:IEEE, 2012:1239-1242.
[47] Zheng C H, LI D W. The value of coronary arteriography in diagnosing coronary heart disease[J]. Shandong Medical Journal, 2005, 45(32):42.
[48] Karimi M, Amirfattahi R, Sadri S, et al. Noninvasive detection and classification of coronary artery occlusions using wavelet analysis of heart sounds with neural networks[C]//London:Medical Applications of Signal Processing, the 3rd IEEE International Seminal. Piscataway NJ:IEEE, 2005:117-120.
[49] Yang W, Fang P. New developments of resting ECG in detecting ventricular function in coronary artery disease[J]. Chinese Journal of Medicine, 2006, 41(1):13-16.
[50] Liu M, Wang Y, Dong X G, et al. Improved BP algorithm and its application to intelligent diagnosis of coronary heart disease[C]//International Conference on Electronic Measurement & Instruments. Piscataway NJ:IEEE, 2011:204-207.
[51] Liu M, He Y D, Wang J, et al. Hybrid intelligent algorithm and its application in geological hazard risk assessment[J]. Neurocomputing, 2015, 149(PB):847-853.
[52] Lazarova V, Manem J. Biofilm characterization and activity analysis in water and wastewater treatment[J]. Water Research, 1995, 29(10):2227-2245.
[53] Lin S, Wang X, Chao Y, et al. Predicting biofilm thickness and biofilm viability based on the concentration of carbon-nitrogen-phosphorus by support vector regression[J]. Environmental Science & Pollution Research, 2015, 23(1):418-425.
[54] 郭婷, 郑颖. 数据挖掘在国内图书情报领域的应用现状分析——基于文献计量分析和共词分析[J]. 情报科学, 2015, 33(10):91-98. Guo Ting, Zheng Ying. Application of data mining in library and information service in china-Based on bibliometric analysis and co-word analysis[J]. Information Science, 2015, 33(10):91-98.
[55] 王光宏, 蒋平. 数据挖掘综述[J]. 同济大学学报(自然科学版), 2004, 32(2):246-252. Wang guanghong, Jiang Ping. Data mining overview[J]. Journal of Tongji University(Science & Technology Edition), 2004, 32(2):264-252.
