Suchergebnisse - stacked denoising autoencoder((sdae OR sae))

Convergence Technology Opportunity Discovery for Firms Based on Technology Portfolio Using the Stacked Denoising AutoEncoder (SDAE)

Autoren: Deuksin Kwon So Young Sohn

Quelle: IEEE Transactions on Engineering Management. 71:1804-1818

Schlagwörter: 0502 economics and business, 05 social sciences

Prediction of Recurrence using a Stacked Denoising Autoencoder and Multifaceted Feature Analysis of Pretreatment MRI in Patients with Nasopharyngeal Carcinoma

Autoren: Yibin, Liu Xianwen, Wang Jiongyi, Li et al.

Quelle: Current Radiopharmaceuticals. 18:224-243

Zugangs-URL: https://pubmed.ncbi.nlm.nih.gov/40237056

Stepwise Inertial Intelligent Control of Wind Power for Frequency Regulation Based on Stacked Denoising Autoencoder and Deep Neural Network

Autoren: WANG Yalun, ZHOU Tao, CHEN Zhong, WANG Yi, QUAN Hao

Quelle: Shanghai Jiaotong Daxue xuebao, Vol 57, Iss 11, Pp 1477-1491 (2023)

Schlagwörter: stepwise inertial control (sic), secondary frequency drop (sfd), sparrow search algorithm (ssa), stacked denoising autoencoder (sdae), deep neural network (dnn), Engineering (General). Civil engineering (General), TA1-2040, Chemical engineering, TP155-156, Naval architecture. Shipbuilding. Marine engineering, VM1-989

Dateibeschreibung: electronic resource

Relation: https://xuebao.sjtu.edu.cn/article/2023/1006-2467/1006-2467-57-11-1477.shtml; https://doaj.org/toc/1006-2467

Zugangs-URL: https://doaj.org/article/5703db5dde17408889132f952768f68b

Prediction of psychophysiological perception of driver in road tunnel using particle swarm optimization improved stacked denoising autoencoder model

Autoren: Can Qin Bo Liang Jia'an Niu et al.

Quelle: Array, Vol 27, Iss , Pp 100475- (2025)

Schlagwörter: Lighting environment of road tunnel, Stacked denoising autoencoder, Particle swarm optimization, Information representation, Psychophysiological perception, Computer engineering. Computer hardware, TK7885-7895, Electronic computers. Computer science, QA75.5-76.95

Dateibeschreibung: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S259000562500102X; https://doaj.org/toc/2590-0056

Zugangs-URL: https://doaj.org/article/42d2b7245a534844bd1edcf6bbf34507

Accurate estimation of state of charge and state of health of electric vehicle power batteries based on dynamic channel pruning informer-stacked denoising autoencoder model.

Autoren: Peng, Ziran Wang, Shunhao Zhang, Shengchun et al.

Quelle: Electrical Engineering. Jan2026, Vol. 108 Issue 1, p1-19. 19p.

Physics-Informed SDAE-Based Denoising Model for High-Impedance Fault Detection

Autoren: Jianxin Lin Xuchang Wang Huaiyuan Wang

Quelle: Processes ; Volume 13 ; Issue 11 ; Pages: 3673

Schlagwörter: high-impedance fault (HIF), distribution network, denoise, stacked denoising autoencoder (SDAE), attention mechanism, energy proportion guidance

Geographisches Schlagwort: agris

Dateibeschreibung: application/pdf

Relation: Energy Systems; https://dx.doi.org/10.3390/pr13113673

Verfügbarkeit: https://doi.org/10.3390/pr13113673

An Anomaly Detection Method for UAV Based on Wavelet Decomposition and Stacked Denoising Autoencoder

Autoren: Shenghan Zhou Zhao He Xu Chen et al.

Quelle: Aerospace, Vol 11, Iss 5, p 393 (2024)

Schlagwörter: anomaly detection, wavelet decomposition, stacked denoising autoencoder (SDAE), UAV flight data, Motor vehicles. Aeronautics. Astronautics, TL1-4050

Dateibeschreibung: electronic resource

Relation: https://www.mdpi.com/2226-4310/11/5/393; https://doaj.org/toc/2226-4310

Zugangs-URL: https://doaj.org/article/b2f8b29b20824d4b8e1f34bc50790953

Traffic Image Analysis Based on Stacked Denoising Autoencoder Neural Network

Autoren: Daehyon Kim

Quelle: Journal of Innovation Information Technology and Application, Vol 5, Iss 2, Pp 183-192 (2023)

Schlagwörter: autoencoding, deep belief network, neural network, Electronic computers. Computer science, 0502 economics and business, 05 social sciences, stacked denoising, 0202 electrical engineering, electronic engineering, information engineering, Information technology, QA75.5-76.95, 02 engineering and technology, T58.5-58.64, backpropagation

Zugangs-URL: https://doaj.org/article/fabc870fc1524bf4a89ecb4aaed0ca7a

Data-Driven Bearing Fault Diagnosis of Microgrid Network Power Device Based on a Stacked Denoising Autoencoder in Deep Learning and Clustering by Fast Search without Data Labels

Autoren: Xiaodi Zhang Fan Xu Xin Shu et al.

Quelle: Complexity, Vol 2020 (2020)

Schlagwörter: Electronic computers. Computer science, 0202 electrical engineering, electronic engineering, information engineering, QA75.5-76.95, 02 engineering and technology

Dateibeschreibung: text/xhtml

Zugangs-URL: https://downloads.hindawi.com/journals/complexity/2020/5013871.pdf
https://doaj.org/article/1c1a5d35d5484f8ea5ad2f4a76ec2885
https://dblp.uni-trier.de/db/journals/complexity/complexity2020.html#XuSLZ20
https://www.hindawi.com/journals/complexity/2020/5013871/
https://scholars.cityu.edu.hk/files/71111528/5013871.pdf
https://downloads.hindawi.com/journals/complexity/2020/5013871.pdf
http://downloads.hindawi.com/journals/complexity/2020/5013871.pdf
https://scholars.cityu.edu.hk/en/publications/datadriven-bearing-fault-diagnosis-of-microgrid-network-power-device-based-on-a-stacked-denoising-autoencoder-in-deep-learning-and-clustering-by-fast-search-without-data-labels(a0409b4d-e1c9-42ef-8fc0-fce4f0118bf5).html

Roller bearing fault diagnosis using stacked denoising autoencoder in deep learning and Gath–Geva clustering algorithm without principal component analysis and data label

Autoren: Fan Xu Wai tai Peter Tse Yiu Lun Tse

Quelle: Applied Soft Computing. 73:898-913

Schlagwörter: 0209 industrial biotechnology, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Zugangs-URL: https://www.sciencedirect.com/science/article/pii/S1568494618305544
https://dblp.uni-trier.de/db/journals/asc/asc73.html#XuTT18
https://doi.org/10.1016/j.asoc.2018.09.037

High-Resolution Remote Sensing Image Zero-Watermarking Algorithm Based on Blockchain and SDAE

Autoren: Dingjie Xu Na Ren Changqing Zhu

Quelle: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 323-339 (2024)

Schlagwörter: InterPlanetary file system (IPFS), Ocean engineering, Blockchain, high-resolution remote sensing images (HRRS), QC801-809, Geophysics. Cosmic physics, stacked denoising autoencoder (SDAE), 0211 other engineering and technologies, 0202 electrical engineering, electronic engineering, information engineering, copyright protection, 02 engineering and technology, TC1501-1800, Hyperledger Fabric

Zugangs-URL: https://doaj.org/article/23bb2a27515440dbac1fedfec1aa0a53

Data-Driven Bearing Fault Diagnosis of Microgrid Network Power Device Based on a Stacked Denoising Autoencoder in Deep Learning and Clustering by Fast Search without Data Labels.

Autoren: Xu, Fan Shu, Xin Li, Xin et al.

Quelle: Complexity; 11/2/2020, p1-29, 29p

Schlagwörter: FAULT diagnosis, MICROGRIDS, DEEP learning, BEARINGS (Machinery), PRINCIPAL components analysis, NONLINEAR functions

Early Warning of Critical Blockage in Coal Mills Based on Stacked Denoising Autoencoders

Autoren: Yanping Li Feng Hong Liang Tian et al.

Quelle: IEEE Access, Vol 8, Pp 176101-176111 (2020)

Schlagwörter: Coal mill, early warning, SDAE, 0202 electrical engineering, electronic engineering, information engineering, Electrical engineering. Electronics. Nuclear engineering, 02 engineering and technology, critical blockage recognition, Mahalanobis distance, 7. Clean energy, TK1-9971

Zugangs-URL: https://ieeexplore.ieee.org/ielx7/6287639/8948470/09205881.pdf
https://doaj.org/article/12982c94ff43405b8b93e89059b980ed
https://dblp.uni-trier.de/db/journals/access/access8.html#LiHTLC20
https://doi.org/10.1109/ACCESS.2020.3026918
https://ieeexplore.ieee.org/document/9205881/

A fault diagnosis framework for rotating machinery of marine equipment: A semi-supervised learning framework based on contractive stacked autoencoder.

Autoren: Pan, Penghao Zhao, Dong Li, Yueyang

Quelle: Proceedings of the Institution of Mechanical Engineers, Part M: Journal of Engineering for the Maritime Environment (Sage Publications, Ltd.); Aug2023, Vol. 237 Issue 3, p625-636, 12p

RHCBAM-based stacked denoising autoencoder for wind turbine misalignment fault detection

Autoren: Dian Long Yancai Xiao Aixin Dai et al.

Quelle: Measurement Science and Technology. 36:086143

Roller bearing fault diagnosis using stacked denoising autoencoder in deep learning and Gath–Geva clustering algorithm without principal component analysis and data label.

Autoren: Xu, Fan Tse, Wai tai Peter Tse, Yiu Lun

Quelle: Applied Soft Computing. Dec2018, Vol. 73, p898-913. 16p.

Schlagwörter: Principal components analysis, Deep learning, Clustering of particles, Debugging, Entropy (Information theory)

Short-Term Wind-Speed Forecasting Based on Multiscale Mathematical Morphological Decomposition, K-Means Clustering, and Stacked Denoising Autoencoders

Autoren: Weichao Dong Hexu Sun Zheng Li et al.

Quelle: IEEE Access, Vol 8, Pp 146901-146914 (2020)

Schlagwörter: multiscale mathematical morphological decomposition, short-term wind-speed forecasting, 0211 other engineering and technologies, 0202 electrical engineering, electronic engineering, information engineering, K-means clustering, Electrical engineering. Electronics. Nuclear engineering, 02 engineering and technology, 7. Clean energy, stacked denoising autoencoders, TK1-9971

Zugangs-URL: https://ieeexplore.ieee.org/ielx7/6287639/8948470/09163090.pdf
https://doaj.org/article/080a81e4e4bd4b88a6dd0f8a63710a2d
https://ieeexplore.ieee.org/document/9163090
https://dblp.uni-trier.de/db/journals/access/access8.html#DongSLZY20
https://doaj.org/article/080a81e4e4bd4b88a6dd0f8a63710a2d

An Analog Circuit Fault Diagnosis Method Incorporating Multi-Objective Selection of Measurement Nodes

Autoren: Yating Chang Xianglian Xu Kaitian Deng et al.

Quelle: Electronics ; Volume 14 ; Issue 8 ; Pages: 1528

Schlagwörter: analog circuit, fault diagnosis, measurement node selection, stacked denoising autoencoder (SDAE), multiple objective beluga whale optimization (MOBWO), adaptive particle swarm optimization (APSO)

Dateibeschreibung: application/pdf

Relation: Power Electronics; https://dx.doi.org/10.3390/electronics14081528

Verfügbarkeit: https://doi.org/10.3390/electronics14081528

Probabilistic Stacked Denoising Autoencoder for Power System Transient Stability Prediction With Wind Farms

Autoren: Tong Su Youbo Liu Junbo Zhao et al.

Quelle: IEEE Transactions on Power Systems. 36:3786-3789

Schlagwörter: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 7. Clean energy

Zugangs-URL: https://ieeexplore.ieee.org/document/9288771

CLPM: A Cooperative Link Prediction Model for Industrial Internet of Things Using Partitioned Stacked Denoising Autoencoder

Autoren: Lanlan Rui Yu Zhu Zhipeng Gao et al.

Quelle: IEEE Transactions on Industrial Informatics. 17:3620-3629

Schlagwörter: 9. Industry and infrastructure, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Zugangs-URL: https://ieeexplore.ieee.org/document/9105066/
https://doi.org/10.1109/TII.2020.2999318
https://dblp.uni-trier.de/db/journals/tii/tii17.html#RuiZGQ21