Suchergebnisse - denoising-stacked autoencoder

Denoising stacked autoencoders‐based near‐infrared quality monitoring method via robust samples evaluation von Lv, Jiapeng, Chen, Zihao, Luan, Xiaoli, Liu, Fei

“… This paper proposes a denoising stacked autoencoders‐based near‐infrared spectroscopy …”
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Denoising stacked autoencoders for transient electromagnetic signal denoising von Lin, Fanqiang, Chen, Kecheng, Wang, Xuben, Cao, Hui, Chen, Danlei, Chen, Fanzeng

“… of the characteristics of the SFS to denoise the SFS. We introduce the SFSDSA (secondary field signal denoising stacked autoencoders …”
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Automated atrial fibrillation classification based on denoising stacked autoencoder and optimized deep network von Singh, Prateek, Sharma, Ambalika, Maiya, Shreesha

“… With this in mind, the two-fold study is proposed, in which three denoising autoencoders for ECG signal pre-processing were evaluated and compared …”
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Building feature space of extreme learning machine with sparse denoising stacked-autoencoder von Cao, Le-le, Huang, Wen-bing, Sun, Fu-chun

“… Deep learning algorithms such as stacked autoencoder (SAE) and deep belief network (DBN) are built on learning several levels of representation of the input …”
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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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Identification Method for Missing Cotter Pins in Catenary Systems Based on Stacked Denoising Autoencoder Network von SHAN Chonghao

“… (stacked denoising autoencoder), thereby achieving efficient detection of missing cotter pins …”
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Deep asset allocation for trend following investing von Kim, Saejoon, Kim, Hyuksoo

“… Trend following strategies are well-known to exhibit excellent excess return performance across a wide range of asset classes in various global markets. For …”
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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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Stepwise Inertial Intelligent Control of Wind Power for Frequency Regulation Based on Stacked Denoising Autoencoder and Deep Neural Network von WANG Yalun, ZHOU Tao, CHEN Zhong, WANG Yi, QUAN Hao

“… Stepwise inertial control (SIC) provides a step-increase of power after load fluctuation, which can effectively prevent system frequency decline and ensure the …”
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Partial Discharge Patterns Recognition of GIS with Denoising-stacked Autoencoder Networks von Zhao, Yiming, Yan, Jing, Wang, Yanxin, Liu, Tingliang, Jiang, Junjie

“… This paper proposes a pattern recognition classifier that directly and automatically selects and classifies fault features by denoising-stacked autoencoder …”
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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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Fault Diagnosis of High-Voltage Circuit Breakers Using Hilbert-Huang Transform and Denoising-Stacked Autoencoder von Yang, Wei, Zhang, Guobao, Song, Dongbo, Cai, Mengyi, Zhao, Hengyang, Yan, Jing

“… Once it fails, it will seriously threaten the safety of the power grid. In this paper, a new high-voltage circuit breaker fault diagnosis algorithm based on denoising-stacked autoencoder is proposed …”
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Data Quality Improvement Method for Power Equipment Condition Based on Stacked Denoising Autoencoders Improved by Particle Swarm Optimization von JI Rong, HOU Huijuan, SHENG Gehao, ZHANG Lijing, SHU Bo, JIANG Xiuchen

“… In order to solve this problem, a data cleaning method based on improved stack noise reduction autoencoder is proposed in this paper …”
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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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Knock-Knock: Acoustic object recognition by using stacked denoising autoencoders von Luo, Shan, Zhu, Leqi, Althoefer, Kaspar, Liu, Hongbin

“… In this paper, stacked denoising autoencoders are applied to train a deep learning model. Knocking each object in our test set 120 times with a marker pen to obtain …”
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Stacked denoising autoencoder‐based feature learning for out‐of‐control source recognition in multivariate manufacturing process von Yu, Jianbo, Zheng, Xiaoyun, Wang, Shijin

“… This paper presents an effective and reliable deep learning method known as stacked denoising autoencoder (SDAE …”
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Deep feature fusion‐based stacked denoising autoencoder for tag recommendation systems von Fei, Zhengshun, Wang, Jinglong, Liu, Kangling, Attahi, Eric, Huang, Bingqiang

“… With the rapid development of artificial intelligence technology, commercial robots have gradually entered our daily lives. In order to promote product …”
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Automated Atrial Fibrillation Classification Based on Denoising Stacked Autoencoder and Optimized Deep Network von Singh, Prateek, Sharma, Ambalika, Maiya, Shreesha

“… Keeping this in mind, we have proposed a two-fold study. First, an end-to-end model is proposed to denoise the electrocardiogram signals using denoising autoencoders (DAE …”
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Automatic Diagnosis of Microgrid Networks’ Power Device Faults Based on Stacked Denoising Autoencoders and Adaptive Affinity Propagation Clustering von Fan, Bo, Zhang, Xiaodi, Shu, Xin, Xu, Fan

“… This paper presents a model based on stacked denoising autoencoders (SDAEs) in deep learning and adaptive affinity propagation (adAP …”
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A novel modulation classification method in cognitive radios using higher-order cumulants and denoising stacked sparse autoencoder von Xu Zhu, Fujii, Takeo

“… We use Stacked Denoising Sparse Autoencoder as a classifier for single-carrier modulation classification …”
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