Art

J-GLOBAL ID：202302222537875004   Reference number：23A1948678

A Fault Diagnosis Model for Tennessee Eastman Processes Based on Feature Selection and Probabilistic Neural Network

特徴選択と確率的ニューラルネットワークに基づくテネシー・イーストマンプロセスのための故障診断モデル【JST・京大機械翻訳】

Author (4)： Xu Haoxiang ,  Ren Tongyao ,  Mo Zhuangda ,  Yang Xiaohui
Material： Applied Sciences (Web)
Volume： 12  Issue： 17  Page： 8868  Publication year： 2022 
JST Material Number： U7135A  ISSN： 2076-3417  Document type： Article
Article type： 原著論文  Country of issue： Switzerland (CHE)  Language： ENGLISH (EN)

Abstract/Point： Since the classification metho...

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Thesaurus term： algorithm ,  optimization ,  simplification ,  redundancy(property) ,  *network ,  optimization method ,  *fault diagnosis ,  *neural network(biomodel) ,  *feature selection ,  artificial intelligence ,  smoothing ,  flight ,  support vector machine
Semi thesaurus term： 収束速度 ,  *確率的ニューラルネットワーク ,  ヒューリスティック最適化 , 【Automatic Indexing@JST】

Author keywords (7)： fault diagnosis ,  probabilistic neural network ,  TE process ,  modified salp swarm algorithm ,  feature selection ,  SVM-RFE ,  PSO-SVM

JST classification (2)： Motors  (NB07030U) ,  Other system programmings  (JD03070M)

Reference (53)：

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Terms in the title (4)： 特徴選択 ,  確率的ニューラルネットワーク ,  故障 ,  診断モデル