Search Results - "Sparse stacked autoencoder network"

Sparse stacked autoencoder network for complex system monitoring with industrial applications

Authors: Keke Huang Ziwei Deng Zhaohui Tang et al.

Source: Chaos, Solitons & Fractals. 137:109838

Subject Terms: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Access URL: http://ui.adsabs.harvard.edu/abs/2020CSF...13709838D/abstract
https://ideas.repec.org/a/eee/chsofr/v137y2020ics0960077920302381.html
https://ui.adsabs.harvard.edu/abs/2020CSF...137j9838D/abstract
https://www.sciencedirect.com/science/article/pii/S0960077920302381

Sparse stacked autoencoder network for complex system monitoring with industrial applications

Authors: Deng, Ziwei Li, Yuxuan Zhu, Hongqiu et al.

Relation: http://www.sciencedirect.com/science/article/pii/S0960077920302381

Availability: http://www.sciencedirect.com/science/article/pii/S0960077920302381

DS2AN: Deep stacked sparse autoencoder for secure and fast authentication in HetNets.

Authors: Hemavathi Akhila, S. Zubeda, Samreen et al.

Source: Security & Privacy; May2022, Vol. 5 Issue 3, p1-18, 18p

Authentication and Resource Allocation Strategies during Handoff for 5G IoVs Using Deep Learning.

Authors: Hemavathi Akhila, Sreenatha Reddy Alotaibi, Youseef et al.

Source: Energies (19961073); Mar2022, Vol. 15 Issue 6, p2006-2006, 27p

Subject Terms: DEEP learning, INTELLIGENT transportation systems, RESOURCE allocation, 5G networks, REINFORCEMENT learning

Network security situation assessment method based on ACDAE-ResBiGRU.

Authors: Li, Binyong Zhang, Jie

Source: Maintenance & Reliability / Eksploatacja i Niezawodność; 2025, Vol. 27 Issue 4, p1-19, 19p

Subject Terms: COMPUTER network security, FEATURE extraction, SITUATIONAL awareness, RISK assessment, RECURRENT neural networks, CLASSIFICATION, ARTIFICIAL neural networks, SIGNAL denoising

Utilizing a Hybrid Cat-Swarm Optimization Algorithm for Seamless Vertical Handoff in Vanet.

Authors: Jahangeer, Naskath Mustafa, Zaid Aldabbas, Hamza

Source: Wireless Personal Communications; Jul2024, Vol. 137 Issue 1, p495-521, 27p

Subject Terms: OPTIMIZATION algorithms, IEEE 802.16 (Standard), UNIVERSAL Mobile Telecommunications System, MULTICASTING (Computer networks), RADIO technology, WIRELESS Internet

Development and trending of deep learning methods for wind power predictions.

Authors: Liu, Hong Zhang, Zijun

Source: Artificial Intelligence Review; May2024, Vol. 57 Issue 5, p1-49, 49p

A Novel Digital Twin Framework for Aeroengine Performance Diagnosis.

Authors: Wang, Zepeng Wang, Ye Wang, Xizhen et al.

Source: Aerospace (MDPI Publishing); Sep2023, Vol. 10 Issue 9, p789, 26p

Subject Terms: DIGITAL twin, BOOSTING algorithms, VALUE engineering, FAULT diagnosis, AIRPLANE motors, ECONOMIC efficiency

Analysis of Gas Turbine Compressor Performance after a Major Maintenance Operation Using an Autoencoder Architecture.

Authors: de Castro-Cros, Martí Velasco, Manel Angulo, Cecilio

Source: Sensors (14248220); Feb2023, Vol. 23 Issue 3, p1236, 11p

Subject Terms: GAS compressors, COMPRESSOR performance, GAS turbines, COMPRESSORS, GAS analysis, MANUFACTURING processes, INDUSTRIAL gases, MACHINE learning

Power Generation Prediction Method of Offshore Wind Turbines Based on Cascaded Deep Learning.

Authors: Sun, Zhen'ao Chen, Zhe

Source: International Transactions on Electrical Energy Systems; 9/23/2022, p1-10, 10p

Subject Terms: WIND turbines, DEEP learning, GREEDY algorithms, WIND power, FORECASTING

A Hierarchical Sparse Discriminant Autoencoder for Bearing Fault Diagnosis.

Authors: Zeng, Mengjie Li, Shunming Li, Ranran et al.

Source: Applied Sciences (2076-3417); Jan2022, Vol. 12 Issue 2, p818, 18p

Subject Terms: FAULT diagnosis, PARTICLE swarm optimization, HIERARCHICAL Bayes model, FEATURE extraction, NETWORK performance, MATHEMATICAL optimization

Company/Entity: CASE Western Reserve University

Predicting Remaining Useful Life of Rolling Bearings Based on Reliable Degradation Indicator and Temporal Convolution Network with the Quantile Regression.

Authors: Tian, Qiaoping Wang, Honglei

Source: Applied Sciences (2076-3417); Jun2021, Vol. 11 Issue 11, p4773, 27p

Subject Terms: ROLLER bearings, TIME-varying networks, FEATURE extraction, DATA reduction, QUANTILE regression, FORECASTING, DATA compression

Automatic classification of nerve discharge rhythms based on sparse auto-encoder and time series feature.

Authors: Jiang, Zhongting Wang, Dong Chen, Yuehui

Source: BMC Bioinformatics; 5/1/2021, Vol. 22 Issue 1, p1-14, 14p

Deep Learning for the Industrial Internet of Things (IIoT): A Comprehensive Survey of Techniques, Implementation Frameworks, Potential Applications, and Future Directions.

Authors: Latif, Shahid Driss, Maha Boulila, Wadii et al.

Source: Sensors (14248220); Nov2021, Vol. 21 Issue 22, p7518, 1p

Subject Terms: INTERNET of things, DEEP learning, ARTIFICIAL intelligence, MANUFACTURING processes, SMART devices, SOFTWARE frameworks