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A Hybrid Feature Selection Based on Ant Colony Optimization and Probabilistic Neural Networks for Bearing Fault Diagnostics

机译：基于蚁群优化和概率神经网络的轴承故障诊断混合特征选择

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Y. H. Gai; G. Yu;
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年度 2015
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1. A hybrid approach for feature subset selection using neural networks and ant colony optimization [J] . Rahul Karthik Sivagaminathan, Sreeram Ramakrishnan Expert systems with applications . 2007,第1期

机译：神经网络和蚁群优化的混合特征子集选择方法
2. FEATURE SELECTION USING MODIFIED ANT COLONY OPTIMIZATION APPROACH (FS-MACO) BASED FIVE LAYERED ARTIFICIAL NEURAL NETWORK FOR CROSS DOMAIN OPINION MINING [J] . DR.E.CHANDRA BLESSIE, S.GNANAPRIYA Journal of Theoretical and Applied Information Technology . 2018,第12期

机译：基于改进蚁群优化方法（FS-MACO）的五层人工神经网络进行跨域意见挖掘的特征选择
3. Fault diagnostics of rolling bearings using feature fusion based BP, RBF and PNN neural networks [J] . Cheng Yuhua, Yin Chun, Bai Libing, International journal of applied electromagnetics and mechanics . 2016,第1a2期

机译：基于特征融合的BP，RBF和PNN神经网络的滚动轴承故障诊断
4. A Hybrid Feature Selection Based on Ant Colony Optimization and Probabilistic Neural Networks for Bearing Fault Diagnostics [C] . Y. H. Gai, G. Yu International Conference on e-Engineering and Digital Enterprise Technology . 2008

机译：基于蚁群优化和概率神经网络的轴承故障诊断的混合特征选择
5. HOPNET: A Hybrid ant colony OPtimization routing algorithm for Mobile ad hoc NETwork [D] . Wang, Jianping 2008

机译：HOPNET：一种用于移动自组织网络的混合蚁群优化路由算法
6. Bearing Fault Diagnosis with a Feature Fusion Method Based on an Ensemble Convolutional Neural Network and Deep Neural Network [O] . Hongmei Li, Jinying Huang, Shuwei Ji 2019

机译：基于集成卷积神经网络和深度神经网络的特征融合方法进行轴承故障诊断
7. A New Hybrid Ant Colony Optimization Based on Brain Storm Optimization for Feature Selection [O] . Haomo LIANG, Zhixue WANG, Yi LIU 2019

机译：基于脑风暴优化的特征选择新的混合蚁群优化

A Hybrid Feature Selection Based on Ant Colony Optimization and Probabilistic Neural Networks for Bearing Fault Diagnostics

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