Search Results - "stack denoising autoencoder"

SDAE-LFM: A Latent Factor Model for Recommendation Based on Stack Denoising AutoEncoder by Luo, Jianyan, Xing, Xing, Zheng, Hang, Xin, Mindong, Jia, Zhichun

“… In order to deal with these problems, we proposed a latent factor model recommendation algorithm based on stack denoising autoencoder (SDAE-LFM…”
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Long baseline underwater source localization based on deep K-Means++ clustering in complex underwater environments by Dai, Yawen, Yang, Lei, Cao, Yifei

“… A three-layer stack denoising autoencoder (SDA) was utilized to extract the features of the trilateration results…”
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BePCon: A Photoplethysmography-based Quality-aware Continuous Beat-to-Beat Blood Pressure Measurement Technique Using Deep Learning by Roy, Monalisa Singha, Gupta, Rajarshi, Sharma, Kaushik Das

“…Research on noninvasive blood pressure (NIBP) measurement using electrocardiogram (ECG)/ photoplethysmogram (PPG) and their combinations have been most popular…”
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An Intelligent Fault Diagnosis Method for Reciprocating Compressors Based on LMD and SDAE by Liu, Yang, Duan, Lixiang, Yuan, Zhuang, Wang, Ning, Zhao, Jianping

“…) and the Stack Denoising Autoencoder (SDAE). The vibration signal is firstly decomposed by LMD and reconstructed…”
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Stack Denoising Autoencoder and State-Space Model Based Bearing RUL Prediction Method by Yang, Lei, Xu, Cuiwentong, Duan, Rongkai, Liao, Yuhe

“… To solve the problems, a RUL prediction method based on stack denoising autoencoder (SDA) and non-overlapping sliding window…”
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On-Device Reliability Assessment and Prediction of Missing Photoplethysmographic Data Using Deep Neural Networks by Singha Roy, Monalisa, Roy, Biplab, Gupta, Rajarshi, Das Sharma, Kaushik

“… This paper describes an on-device reliability assessment from PPG measurements using a stack denoising autoencoder (SDAE…”
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A Hybrid Three-Staged, Short-Term Wind-Power Prediction Method Based on SDAE-SVR Deep Learning and BA Optimization by Duan, Ruiqin, Peng, Xiaosheng, Li, Cong, Yang, Zimin, Jiang, Yan, Li, Xiufeng, Liu, Shuangquan

“…Wind power prediction (WPP) is necessary to the safe operation and economic dispatch of power systems. In order to improve the prediction accuracy of WPP, in…”
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Nondestructive detection of cadmium content in oilseed rape leaves under different silicon environments using deep transfer learning and Vis-NIR hyperspectral imaging by Zhou, Xin, Liu, Yang, Zhao, Chunjiang, Sun, Jun, Shi, Lei, Cong, Sunli

“…In this paper, a transfer stack denoising autoencoder (T-SDAE) algorithm is proposed to implement the migration of cadmium (Cd…”
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Yield and Properties Prediction Based on the Multicondition LSTM Model for the Solvent Deasphalting Process by Long, Jian, Chen, Yifan, Cao, Dengke, Chen, Pengyu, Yang, Minglei

“… Then, the stack denoising autoencoder (SDAE) is used to reconstruct the data and obtain the nonlinear mapping information of hidden layers of SDAE and achieve feature dimension reduction…”
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Flight delay prediction based on deep learning and Levenberg-Marquart algorithm by Yazdi, Maryam Farshchian, Kamel, Seyed Reza, Chabok, Seyyed Javad Mahdavi, Kheirabadi, Maryam

“…Flight delay is inevitable and it plays an important role in both profits and loss of the airlines. An accurate estimation of flight delay is critical for…”
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Marginalised stack denoising autoencoders for metagenomic data binning by Kouchaki, Samaneh, Tirunagari, Santosh, Tapinos, Avraam, Robertson, David L.

“…Shotgun sequencing has facilitated the analysis of complex microbial communities. Recently we have shown how local binary patterns (LBP) from image processing…”
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A Deep Learning Model to Predict the ncRNA-Protein Interactions Based on Sequences Information Only by Sewailem, Maha FM, Arif, Muhammad, Alam, Tanvir

“…Noncoding RNAs (ncRNAs) play significant roles in multiple fundamental biological processes, in particular, ncRNAs interactions provide valuable insights into…”
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Research on tool condition monitoring (TCM) using a novel unsupervised deep neural network (DNN) by Gao, Jingjing, Liu, Jing, Yu, Xinli

“…) based on stack denoising autoencoder (SDA) is proposed. After feature extraction and selection, the stack denoising automatic coding network reduces the dimensionality of the feature vector…”
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Intelligent Fault Diagnosis Method for Blade Damage of Quad-Rotor UAV Based on Stacked Pruning Sparse Denoising Autoencoder and Convolutional Neural Network by Yang, Pu, Wen, Chenwan, Geng, Huilin, Liu, Peng

“…). This method processes the original input data by using a stack denoising autoencoder. Different from the traditional autoencoder, stack pruning sparse denoising…”
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Research on tool condition monitoring by Gao, Jingjing, Liu, Jing, Yu, Xinli

“…) based on stack denoising autoencoder (SDA) is proposed. After feature extraction and selection, the stack denoising automatic coding network reduces the dimensionality of the feature vector…”
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Network intrusion detection based on Contractive Sparse Stacked Denoising Autoencoder by Lu, Jizhao, Meng, Huiping, Li, Wencui, Liu, Yue, Guo, Yihao, Yang, Yang

“… identify and classify network intrusion data, this paper proposes a Contractive Sparse Stack Denoising Autoencoder(CSSDAE…”
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A Study on Semantic Classification of Guangxi Ethnic Folk Dance Movements Incorporating Deep Learning by Zhang, Zhengwu

“… The research of Guangxi’s national folk dance is currently in a booming period. The research is based on deep learning theory, using stack denoising autoencoder…”
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A Multi-Factor Driven Model for Locomotive Axle Temperature Prediction Based on Multi-Stage Feature Engineering and Deep Learning Framework by Yan, Guangxi, Bai, Yu, Yu, Chengqing, Yu, Chengming

“…Recently, with the increasing scale of the volume of freight transport and the number of passengers, the study of railway vehicle fault diagnosis and condition…”
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Rapid evaluation method for the carrying capacity of 5G base station load scale connected to the distribution network by Tian, Tian, Xu, Yang, Xu, Daolin, Liu, Chao, Li, Tao, Chen, Xin

“… Firstly, the power consumption of 5G base stations was modeled; Secondly, a stack denoising autoencoder model is adopted to achieve fast power flow calculation in the distribution network…”
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Pipeline Leak Diagnosis Based on SDAE by Lang, Xianming, Sui, Dongye, Lv, Yuanhao, Yuan, Kaixin, Zhang, He

“… Then, the feature extraction of two-dimensional feature gray image is carried out by the stack denoising autoencoder…”
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