[1]张龙, 张磊, 熊国良,等. 二叉树型多分类器融合的轴承故障诊断方法[J]. 计算机工程与应用, 2015, 51(21):243-249.
ZHANG Long, ZHANG Lei, XIONG Guoliang, et al. Method of Binary Tree Structure Based Multiple Classifier Fusion in Bearing Fault Diagnosis[J]. Computer Engineering and Application, 2015, 51(21):243-249.
[2]LIU Xiaofeng, BO Lin. Identification of Resonance States of Rotor-bearing System Using RQA and Optimal Binary Tree SVM[J]. Neurocomputering, 2015, 152:36-44.
[3]陈星, 严华. 二叉树SVM算法在小样本故障诊断中的优化[J]. 计算机测量与控制, 2015, 23(3):689-692.
CHEN Xing, YAN Hua. Optimization of BT-SVM for Small Sample Fault Diagnosis[J]. Computer Measurement & Control,2015, 23(3):689-692.
[4]曹苏群, 王士同, 陈晓峰. 基于后验概率的不平衡数据集特征选择算法[J]. 计算机工程, 2008, 34(19):1-3.
CAO Suqun,WANG Shitong, CHEN Xiaofeng. Posterior-probability-based Feature Selection Algorithm for Imbalanced Datasets[J]. Computer Engineering, 2008, 34(19):1-3.
[5]袁广林, 薛模根, 韩裕生,等. 基于自适应多特征融合的mean shift目标跟踪[J]. 计算机研究与发展, 2010, 47(9):1663-1671.
YUAN Guanglin, XUE Mogen, HAN Yusheng, et al. Mean Shift Object Tracking Based on Adaptive Multi-features Fusion[J]. Journal of Computer Research and Development, 2010, 47(9):1663-1671.
[6]张秋余, 赵付清, 王静,等. C-SVM在不同类别样本数目不均衡下的优化[J]. 兰州理工大学学报, 2007, 33(4):90-92.
ZHANG Qiuyu, ZHAO Fuqing, WANG Jing, et al. Optimization of C-SVM in Case of Samples with Unequal Numbers in Their Different Varieties[J]. Journal of Lanzhou University of Technology, 2007, 33(4):90-92.
[7]刘涌, 李海潮, 赵鞭. 一种基于二叉树的测控设备故障诊断方法[J]. 电讯技术, 2016, 56(8):928-933.
LIU Yong, LI Haichao, ZHAO Bian. A Fault Diagnosis Method for TT&C Equipment Based on Binary Tree[J]. Telecommunication Engineering, 2016, 56(8):928-933.
[8]冯育强, 董佳华. 无穷维空间中有界闭凸集的一个反例[J]. 高师理科学刊, 2017, 37(2):4-5.
FENG Yuqiang, DONG Jiahua. A Counterexample of Bounded Closed Convex Set in Infinite Dimensional Space[J]. Journal of Science of Teachers' College and University, 2017, 37(2):4-5.
[9]DURRANT R J. When Is ‘Nearest Neighbour' Meaningful: a Converse Theorem and Implications[J]. Journal of Complexity, 2009, 25(4):385-397.
[10]MIL'MAN V D. New Proof of the Theorem of A. Dvoretzky on Intersection of Convex Bodies[J]. Function Analysis and Its Application, 1971,5(4):288-295.
[11]FRANOIS D, WERTZ V, VERLEYSEN M. Non-Euclidean Metrics for Similarity Search in Noisy Datasets[C]//The 13th European Symposium on Artificial Neural Networks. Bruges, 2005: 339-344.
[12]HSU C M, CHEN M S. On the Design and Applicability of Distance Functions in High-dimensional Data Space[J]. IEEE Transactions on Knowledge & Data Engineering, 2009, 21(4):523-536.
[13]HINNEBURG A, AGGARWAL C C, KEIM D A. What Is the Nearest Neighbor in High Dimensional Spaces?[C]//The 26th VLDB Conference. Cario, 2000:506-515.
[14]AGGARWAL C C, HINNEBURG A,KEIM D A. On the Surprising Behavior of Distance Metrics in High Dimensional Spaces[C]//The 8th International Conference on Database Theory. London, 2001:420-434.
[15]赵莹. 支持向量机中高斯核函数的研究[D]. 上海:华东师范大学, 2007.
ZHAO Ying. The Study on Gauss Kernel Function in Support Vector Machine[D]. Shanghai: East China Normal University, 2007.
[16]李状, 柳亦兵, 滕伟,等. 基于粒子群优化KFCM的风电齿轮箱故障诊断[J]. 振动、测试与诊断, 2017, 37(3):484-488.
LI Zhuang,LIU Yibing,TENG Wei,et al. Fault Diagnosis of Wind Turbine Gearbox Based on KFCM Optimized by Particle Swarm Optimization[J]. Journal of Vibration Measurement & Diagnosis, 2017, 37(3):484-488.
[17]郑波, 高峰. 基于S-PSO分类算法的故障诊断方法[J]. 航空学报, 2015, 36(11):3640-3651.
ZHENG Bo, GAO Feng. Fault Diagnosis Method Based on S-PSO Classification Algorithm[J]. Acta Aeronautica et Astronautica Sinica, 2015, 36(11):3640-3651. |