Výsledky vyhledávání - supervised sparse‐autoencoder‐based deep neural network~

Sparse Autoencoder-based Multi-head Deep Neural Networks for Machinery Fault Diagnostics with Detection of Novelties Autor Yang, Zhe, Gjorgjevikj, Dejan, Long, Jianyu, Zi, Yanyang, Zhang, Shaohui, Li, Chuan

“… To this end, a sparse autoencoder-based multi-head Deep Neural Network (DNN) is presented to jointly learn a shared encoding representation for both unsupervised reconstruction and supervised classification of the monitoring data…”
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Sparse Autoencoder-based Multi-head Deep Neural Networks for Machinery Fault Diagnostics with Detection of Novelties Autor Zhe Yang, Dejan Gjorgjevikj, Jianyu Long, Yanyang Zi, Shaohui Zhang, Chuan Li

“… of novelties.To this end,a sparse autoencoder-based multi-head Deep Neural Network(DNN)is presented to jointly learn a shared encoding representation for both unsupervised reconstruction and supervised classification of the monitoring…”
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SSAE‐MLP: Stacked sparse autoencoders‐based multi‐layer perceptron for main bearing temperature prediction of large‐scale wind turbines Autor Xiao, Xiaocong, Liu, Jianxun, Liu, Deshun, Tang, Yufei, Dai, Juchuan, Zhang, Fan

“… To achieve the goal, this paper proposes a novel deep learning approach named stacked sparse autoencoder multi‐layer perceptron (SSAE‐MLP…”
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Rock mass type prediction for tunnel boring machine using a novel semi-supervised method Autor Yu, Honggan, Tao, Jianfeng, Qin, Chengjin, Xiao, Dengyu, Sun, Hao, Liu, Chengliang

“…•A novel semi-supervised framework is proposed to predict geological type ahead of tunnel face…”
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Intelligent Bearing Fault Diagnosis Method Combining Compressed Data Acquisition and Deep Learning Autor Sun, Jiedi, Yan, Changhong, Wen, Jiangtao

“… Inspired by the idea of compressed sensing and deep learning, a novel intelligent diagnosis method is proposed for fault identification of rotating machines…”
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Machine learning : a Bayesian and optimization perspective Autor Theodoridis, Sergios

“…/Bayesian learning, as well as short courses on sparse modeling, deep learning, and probabilistic graphical models…”
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