Výsledky vyhledávání - "Stack denoising autoencoder"

Automatic fault diagnosis of rolling bearings under multiple working conditions based on unsupervised stack denoising autoencoder

Autoři: Lei Wang Hang Rao Zhengcheng Dong a další

Zdroj: Structural Health Monitoring. 23:3084-3104

Témata: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Stack Denoising Autoencoder and State-Space Model Based Bearing RUL Prediction Method

Autoři: Lei Yang Cuiwentong Xu Rongkai Duan a další

Zdroj: 2022 International Conference on Sensing, Measurement & Data Analytics in the era of Artificial Intelligence (ICSMD). :1-6

Intelligent Pre-warning Method of Transmission Line Icing Based on Stack Denoising Autoencoder

Autoři: Chunyi Wang Wei Liu Heng Zhou a další

Zdroj: Lecture Notes in Electrical Engineering ISBN: 9789819938872

Correction to: A Multi-stack Denoising Autoencoder for QoS Prediction

Autoři: Mengwei Wu Qin Lu Yingxue Wang

Zdroj: Lecture Notes in Computer Science ISBN: 9783031159305

A Multi-stack Denoising Autoencoder for QoS Prediction

Autoři: Mengwei Wu Qin Lu Yingxue Wang

Zdroj: Lecture Notes in Computer Science ISBN: 9783031159305

SDAE-LFM: A Latent Factor Model for Recommendation Based on Stack Denoising AutoEncoder

Autoři: Zhichun Jia Jianyan Luo Mindong Xin a další

Zdroj: Journal of Physics: Conference Series. 1646:012151

Témata: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Přístupová URL adresa: http://ui.adsabs.harvard.edu/abs/2020JPhCS1646a2151L/abstract

Automatic fault diagnosis of rolling bearings under multiple working conditions based on unsupervised stack denoising autoencoder.

Autoři: Wang, Lei Rao, Hang Dong, Zhengcheng a další

Zdroj: Structural Health Monitoring; Sep2024, Vol. 23 Issue 5, p3084-3104, 21p

Témata: AUTOENCODERS, DEEP learning, ROLLER bearings, DIAGNOSIS, ALGORITHMS, FEATURE extraction

A Hybrid Three-Staged, Short-Term Wind-Power Prediction Method Based on SDAE-SVR Deep Learning and BA Optimization

Autoři: Ruiqin Duan Xiaosheng Peng Cong Li a další

Zdroj: IEEE Access, Vol 10, Pp 123595-123604 (2022)

Témata: bat optimization algorithm, Stack denoising autoencoder, 0211 other engineering and technologies, 0202 electrical engineering, electronic engineering, information engineering, Electrical engineering. Electronics. Nuclear engineering, 02 engineering and technology, 7. Clean energy, wind power prediction, TK1-9971

Přístupová URL adresa: https://doaj.org/article/586005aa63424fbcb4d401df2e9c8da3

An Intelligent Fault Diagnosis Method for Reciprocating Compressors Based on LMD and SDAE

Autoři: Yang Liu Lixiang Duan Zhuang Yuan a další

Zdroj: Sensors, Vol 19, Iss 5, p 1041 (2019)

Témata: reciprocating compressor, deep learning, stack denoising autoencoder, local mean decomposition, fault diagnosis, Chemical technology, TP1-1185

Relation: http://www.mdpi.com/1424-8220/19/5/1041; https://doaj.org/toc/1424-8220; https://doaj.org/article/581b77e33d6b4e1ebc7b1007ec176339

Dostupnost: https://doi.org/10.3390/s19051041
https://doaj.org/article/581b77e33d6b4e1ebc7b1007ec176339

A Deep Learning Model to Predict the ncRNA-Protein Interactions Based on Sequences Information Only.

Autoři: Sewailem, Maha FM Arif, Muhammad Alam, Tanvir

Zdroj: Bioinformatics & Biology Insights; 11/10/2025, Vol. 19, p1-12, 12p

Multimodal Deep Learning for Alzheimer’s Disease Diagnosis: Integrating Neuroimaging and Genetic Data.

Autoři: Rahman, Md Jubaer Nipa, Romana Nourin

Zdroj: Journal of Computer Science & Technology Studies; Mar/Apr2025, Vol. 7 Issue 2, p284-293, 10p

Témata: SINGLE nucleotide polymorphisms, ALZHEIMER'S disease, AUTOENCODERS, SUPPORT vector machines, K-nearest neighbor classification, DEEP learning

A Multi-Dimensional Evaluation Method of Collaborative Learning Quality in Higher Education Based on Random Forest.

Autoři: Wang, Haozeng Li, Jiahuan

Zdroj: International Journal of High Speed Electronics & Systems. Dec2025, Vol. 34 Issue 4, p1-21. 21p.

Témata: *ARTIFICIAL neural networks, *CONVOLUTIONAL neural networks, *RANDOM forest algorithms, *AUTOENCODERS, *COLLABORATIVE learning

Long baseline underwater source localization based on deep K-Means++ clustering in complex underwater environments.

Autoři: Dai, Yawen Yang, Lei Cao, Yifei

Zdroj: Digital Signal Processing. Sep2025, Vol. 164, pN.PAG-N.PAG. 1p.

Témata: *LEAST squares, *AUTOENCODERS, *FEATURE extraction, *LOCATION analysis, *CLUSTER analysis (Statistics)

Multimodal Deep Learning for Alzheimer’s Disease Diagnosis: Integrating Neuroimaging and Genetic Data

Autoři: Md Jubaer Rahman Romana Nourin Nipa

Zdroj: Journal of Computer Science and Technology Studies; Vol. 7 No. 2; 284-293; 2709-104X

Témata: Deep Learning, Alzheimer’s Disease, Alzheimer's Disease Neuroimaging Initiative (ADNI), Genetic Data, cognitively normal (CN)., info:eu-repo/semantics/article, info:eu-repo/semantics/publishedVersion

URL: https://al-kindipublisher.com/index.php/jcsts/article/view/9204
https://al-kindipublisher.com/index.php/jcsts/article/view/9204/7882
https://al-kindipublisher.com/index.php/jcsts/article/view/9204/7882

On-Device Reliability Assessment and Prediction of Missing Photoplethysmographic Data Using Deep Neural Networks.

Autoři: Singha Roy, Monalisa Roy, Biplab Gupta, Rajarshi a další

Zdroj: IEEE Transactions on Biomedical Circuits & Systems; Dec2020, Vol. 14 Issue 6, p1323-1332, 10p

A Multi-Factor Driven Model for Locomotive Axle Temperature Prediction Based on Multi-Stage Feature Engineering and Deep Learning Framework.

Autoři: Yan, Guangxi Bai, Yu Yu, Chengqing a další

Zdroj: Machines; Sep2022, Vol. 10 Issue 9, p759-N.PAG, 24p

Témata: REINFORCEMENT learning, DEEP reinforcement learning, FEATURE selection, FREIGHT & freightage, AUTOENCODERS, DEEP learning

Deep Learning Applications in Personal Credit Risk Assessment: Insights from Big Data in Banking

Autoři: Gupta, Neha Sharma, Kritika Verma, Siddharth

Zdroj: Journal of Economic Theory and Business Management; Vol. 1 No. 3 (2024); 37-42; 3006-4961; 3006-4953

Témata: Big Data, Credit Risk Assessment, Deep Learning, Financial Institutions, Peer-reviewed Article

URL: https://www.suaspress.org/ojs/index.php/JETBM/article/view/v1n3a06
https://worldcat.org/search?q=on:HKSUA+https://www.suaspress.org/ojs/index.php/index/oai+JETBM+CNTCOLL
https://www.suaspress.org/ojs/index.php/JETBM/article/view/v1n3a06/v1n3a06
https://www.suaspress.org/ojs/index.php/JETBM/article/view/v1n3a06/v1n3a06
info:eu-repo/grantAgreement

Research on tool condition monitoring (TCM) using a novel unsupervised deep neural network (DNN).

Autoři: Jingjing Gao Jing Liu Xinli Yu

Zdroj: Journal of Vibroengineering. Feb2024, Vol. 26 Issue 1, p193-208. 16p.

Témata: *ARTIFICIAL neural networks, *FEATURE extraction, *AUTOENCODERS, *PRINCIPAL components analysis, *LINEAR network coding

Prediction of performance parameters of a hermetic reciprocating compressor applying an artificial neural network.

Autoři: Bacak, Aykut Çolak, Andaç Batur Dalkılıç, Ahmet Selim

Zdroj: Proceedings of the Institution of Mechanical Engineers: Part E: Journal of Process Mechanical Engineering (Sage Publications, Ltd.); Dec2025, Vol. 239 Issue 6, p3528-3539, 12p

A deep learning framework with hybrid stacked sparse autoencoder for type 2 diabetes prediction.

Autoři: Abdussamad Daud, Hanita Sokkalingam, Rajalingam a další

Zdroj: Scientific Reports; 10/21/2025, Vol. 15 Issue 1, p1-22, 22p

Témata: TYPE 2 diabetes, FEATURE selection, FORECASTING, COMPUTER performance, ARTIFICIAL neural networks, MEDICAL care, DEEP learning