Suchergebnisse - "Stacked denoising autoencoder"

Fault diagnosis of rotary machinery components using a stacked denoising autoencoder-based health state identification von Lu, Chen, Wang, Zhen-Ya, Qin, Wei-Li, Ma, Jian

“… improvements, and economical efficiency. This paper investigates an effective and reliable deep learning method known as stacked denoising autoencoder (SDA …”
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Automated feature learning for nonlinear process monitoring – An approach using stacked denoising autoencoder and k-nearest neighbor rule von Zhang, Zehan, Jiang, Teng, Li, Shuanghong, Yang, Yupu

“… •Automated feature learning based on stacked denoising autoencoder (SDAE) and k-nearest neighbor rule (kNN …”
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A sparse stacked denoising autoencoder with optimized transfer learning applied to the fault diagnosis of rolling bearings von Sun, Meidi, Wang, Hui, Liu, Ping, Huang, Shoudao, Fan, Peng

“… •Fault diagnosis by stacked autoencoder requires less professional knowledge.•Domain adaptation by optimized transfer learning reduces the algorithm’s …”
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Remote Sensing Image Classification Based on Stacked Denoising Autoencoder von Liang, Peng, Shi, Wenzhong, Zhang, Xiaokang

“… is proposed, which is based on Stacked Denoising Autoencoder. First, the deep network model is built through the stacked layers of Denoising Autoencoder …”
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Probabilistic Stacked Denoising Autoencoder for Power System Transient Stability Prediction With Wind Farms von Su, Tong, Liu, Youbo, Zhao, Junbo, Liu, Junyong

“… To address the uncertainties of renewable energy and loads in transient stability assessment with credible contingencies, this letter proposes a stacked denoising autoencoder (SDAE …”
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Multimode process monitoring based on hierarchical mode identification and stacked denoising autoencoder von Gao, Huihui, Wei, Chen, Huang, Wenjie, Gao, Xuejin

“… •A novel hierarchical mode identification strategy is proposed for multimode process.•An improved density peaks clustering algorithm called LDRSDPC is …”
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Roller bearing fault diagnosis using stacked denoising autoencoder in deep learning and Gath–Geva clustering algorithm without principal component analysis and data label von Xu, Fan, Tse, Wai tai Peter, Tse, Yiu Lun

“… Most deep learning models such as stacked autoencoder (SAE) and stacked denoising autoencoder (SDAE …”
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Intelligent fault diagnosis approach with unsupervised feature learning by stacked denoising autoencoder von Xia, Min, Li, Teng, Liu, Lizhi, Xu, Lin, de Silva, Clarence W

“… ) based on stacked denoising autoencoder. Representative features are learned by applying the denoising autoencoder to the unlabelled data in an unsupervised manner …”
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Intelligent analysis of tool wear state using stacked denoising autoencoder with online sequential-extreme learning machine von Ou, Jiayu, Li, Hongkun, Huang, Gangjin, Yang, Guowei

“… •An efficient OS-ELM algorithm is proposed to identify tool wear state.•A SDAE neural network is designed to reduce the samples dimension.•Spindle current …”
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An Anomaly Detection Method for UAV Based on Wavelet Decomposition and Stacked Denoising Autoencoder von Zhou, Shenghan, He, Zhao, Chen, Xu, Chang, Wenbing

“… The paper proposes an anomaly detection method for UAVs based on wavelet decomposition and stacked denoising autoencoder …”
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Enhanced Stacked Denoising Autoencoder-Based Feature Learning for Recognition of Wafer Map Defects von Yu, Jianbo

“… This paper proposes an effective deep learning method, enhanced stacked denoising autoencoder (ESDAE …”
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Convergence Technology Opportunity Discovery for Firms Based on Technology Portfolio Using the Stacked Denoising AutoEncoder (SDAE) von Kwon, Deuksin, Sohn, So Young

“… The present research, by employing a stacked denoising autoencoder, a deep neural network-based collaborative filtering method, provides reliable latent preference toward convergence technology for individual firms …”
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Stacked denoising autoencoder based fault location in voltage source converters‐high voltage direct current von Luo, Guomin, Cheng, Mengxiao, Hei, Jiaxin, Wang, Xiaojun, Huang, Weibo, He, Jinghan

“… A stacked denoising autoencoder based fault location method for high voltage direct current transmission systems is proposed …”
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Gated relational stacked denoising autoencoder with localized author embedding for global citation recommendation von Dai, Tao, Yan, Wenjun, Zhang, Kaiqi, Qiu, Chen, Zhao, Xiangmo, Pan, Shirui

“… This paper presents a novel neural network based model, called gated relational probabilistic stacked denoising autoencoder with localized author (GRSLA …”
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SDARE: A stacked denoising autoencoder method for game dynamics network structure reconstruction von Huang, Keke, Li, Shuo, Dai, Penglin, Wang, Zhen, Yu, Zhaofei

“… Complex network is a general model to represent the interactions within technological, social, information, and biological interaction. Often, the direct …”
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A Robust Wi-Fi Fingerprint Positioning Algorithm Using Stacked Denoising Autoencoder and Multi-Layer Perceptron von Wang, Rongrong, Li, Zhaohui, Luo, Haiyong, Zhao, Fang, Shao, Wenhua, Wang, Qu

“… (Stacked Denoising Autoencoder)-based feature extraction method, which can obtain a robust and time-independent Wi-Fi fingerprint by learning the reconstruction distribution from a raw Wi-Fi signal and an artificial-noise-added Wi-Fi signal …”
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Visual saliency detection via invariant feature constrained stacked denoising autoencoder von Ma, Yunpeng, Yu, Zhihong, Zhou, Yaqin, Xu, Chang, Yu, Dabing

“… In order to solve this problem, a visual saliency detection method based on scale invariant feature and stacked denoising autoencoder is proposed …”
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Deep learning for electrolysis process anode effect prediction based on long short-term memory network and stacked denoising autoencoder von Yin, Gang, Li, Yi-Hui, Yan, Fei-Ya, Quan, Peng-Cheng, Wang, Min, Cao, Wen-Qi, Xu, Heng-Quan, Lu, Jian, He, Wen

“… A stacked denoising autoencoder is utilized to denoise and extract features from a large number of long-period parameter data …”
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Multiscale intelligent fault detection system based on agglomerative hierarchical clustering using stacked denoising autoencoder with temporal information von Yu, Jianbo, Yan, Xuefeng

“… In this study, the interpretability and suitability of stacked denoising autoencoder (SDAE) in process monitoring territory are theoretically analyzed and validated …”
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HFO Detection in Epilepsy: A Stacked Denoising Autoencoder and Sample Weight Adjusting Factors-Based Method von Wu, Min, Qin, Hongzhen, Wan, Xiongbo, Du, Yuxiao

“… To solve these problems, we put forward a novel method to accurately detect HFOs based on the stacked denoising autoencoder (SDAE …”
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