Search Results - "stacked pruning sparse denoising autoencoder"

Intelligent Fault Diagnosis Method for Blade Damage of Quad-Rotor UAV Based on Stacked Pruning Sparse Denoising Autoencoder and Convolutional Neural Network

Authors: Pu Yang Chenwan Wen Huilin Geng et al.

Source: Machines, Vol 9, Iss 12, p 360 (2021)

Subject Terms: intelligent fault diagnosis, stacked pruning sparse denoising autoencoder, convolutional neural network, anti-noise, Mechanical engineering and machinery, TJ1-1570

File Description: electronic resource

Relation: https://www.mdpi.com/2075-1702/9/12/360; https://doaj.org/toc/2075-1702

Access URL: https://doaj.org/article/57fd1ddf636d4ff7816cfd2cd17bcfcf

Stacked pruning sparse denoising autoencoder based intelligent fault diagnosis of rolling bearings

Authors: Haiping Zhu Jiaxin Cheng Cong Zhang et al.

Source: Applied Soft Computing. 88:106060

Subject Terms: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 16. Peace & justice

Access URL: https://www.sciencedirect.com/science/article/pii/S1568494619308439
https://dblp.uni-trier.de/db/journals/asc/asc88.html#ZhuCZWS20
https://jglobal.jst.go.jp/en/detail?JGLOBAL_ID=202002290341314510

RETRACTED: A Novel Day- ahead Electricity Price Forecasting Using multi-modal combined Integration via Stacked Pruning Sparse Denoising Auto Encoder

Authors: Leiming Li Sara Saeedi Bingquan Liu et al.

Source: Energy Reports, Vol 7, Iss, Pp 2201-2213 (2021)

Subject Terms: Electricity Price Forecasting, Sufficient Dimension Reduction, 0211 other engineering and technologies, 0202 electrical engineering, electronic engineering, information engineering, Deep Neural Network, Electrical engineering. Electronics. Nuclear engineering, 02 engineering and technology, Stacked pruning sparse denoising autoencoder, Maximum Separation Subspace, 7. Clean energy, Tensor Canonical Correlation Analysis, TK1-9971

Access URL: https://doaj.org/article/3b490787f5db41ffbe39b973c6cbc800
https://www.sciencedirect.com/science/article/abs/pii/S2352484721002249
https://www.sciencedirect.com/science/article/pii/S2352484721002249

Stacked pruning sparse denoising autoencoder based intelligent fault diagnosis of rolling bearings.

Authors: Zhu, Haiping Cheng, Jiaxin Zhang, Cong et al.

Source: Applied Soft Computing. Mar2020, Vol. 88, pN.PAG-N.PAG. 1p.

Subject Terms: Fault diagnosis, Pruning, Knowledge transfer, Information networks, Intelligent transportation systems, Bears, Redundancy in engineering, Video coding

Deep Learning-Based Machinery Fault Diagnostics

Contributors: Chen, Hongtian Zhong, Kai Ran, Guangtao et al.

Subject Terms: process monitoring, dynamics, variable time lag, dynamic autoregressive latent variables model, sintering process, hammerstein output-error systems, auxiliary model, multi-innovation identification theory, fractional-order calculus theory, canonical variate analysis, disturbance detection, power transmission system, k-nearest neighbor analysis, statistical local analysis, intelligent fault diagnosis, stacked pruning sparse denoising autoencoder, convolutional neural network, anti-noise, flywheel fault diagnosis, belief rule base, fuzzy fault tree analysis, Bayesian network, evidential reasoning, aluminum reduction process, alumina concentration, subspace identification, distributed predictive control, spatiotemporal feature fusion, gated recurrent unit, attention mechanism

File Description: application/octet-stream

Relation: ONIX_20221025_9783036551739_23; https://mdpi.com/books/pdfview/book/6065

Availability: https://directory.doabooks.org/handle/20.500.12854/93169
https://hdl.handle.net/20.500.12854/93169
https://mdpi.com/books/pdfview/book/6065

Intelligent Fault Diagnosis Method for Blade Damage of Quad-Rotor UAV Based on Stacked Pruning Sparse Denoising Autoencoder and Convolutional Neural Network.

Authors: Yang, Pu Wen, Chenwan Geng, Huilin et al.

Source: Machines; Dec2021, Vol. 9 Issue 12, p360-360, 1p

Subject Terms: CONVOLUTIONAL neural networks, FAULT diagnosis, ARTIFICIAL neural networks, DIAGNOSIS, DEEP learning, DRONE aircraft

A Comparative Study of Lightweight, Sparse Autoencoder-Based Classifiers for Edge Network Devices: An Efficiency Analysis of Feed-Forward and Deep Neural Networks.

Authors: Jo, Mi Young Kim, Hyun Jung

Source: Sensors (14248220); Oct2025, Vol. 25 Issue 20, p6439, 22p

Subject Terms: EDGE computing, AUTOENCODERS, RESEARCH evaluation, ANOMALY detection (Computer security), FEEDFORWARD neural networks, ARTIFICIAL neural networks

Forecasting electricity prices in the spot market utilizing wavelet packet decomposition integrated with a hybrid deep neural network.

Authors: Heping Jia Yuchen Guo Xiaobin Zhang et al.

Source: Global Energy Interconnection; Oct2025, Vol. 8 Issue 5, p874-890, 17p

Subject Terms: ELECTRICITY pricing, FORECASTING, FREQUENCY-domain analysis, CONVOLUTIONAL neural networks, LONG short-term memory, DEEP learning, MARKET volatility

A Multi-Sensor and PCSV Asymptotic Classification Method for Additive Manufacturing High Precision and Efficient Fault Diagnosis.

Authors: Wang, Lingfeng Li, Dongbiao Xing, Fei et al.

Source: Structural Durability & Health Monitoring (SDHM); 2025, Vol. 19 Issue 5, p1183-1201, 19p

Subject Terms: FAULT diagnosis, SUPPORT vector machines, ONLINE monitoring systems, MULTIVARIATE analysis, STATISTICAL accuracy, SOLID freeform fabrication, SENSOR networks

Vibration Characteristic Analysis and Dynamic Reliability Modeling of Multi-Rotor UAVs.

Authors: Zhou, Keyi Zhou, Di Wang, Xiru et al.

Source: Machines; Aug2025, Vol. 13 Issue 8, p697, 26p

Subject Terms: ROTOR dynamics, FLUID-structure interaction, MECHANICAL vibration research, DRONE aircraft control systems, FAULT tolerance (Engineering), STATISTICAL reliability, ENGINEERING reliability theory

Intelligent Fault Diagnosis of Rolling Bearings in Strong Noise Environment: An Attention-Driven Hybrid Model Based on IENEMD and Parallel Multiscale CNN.

Authors: Yin, Chen Lee, Heow Pueh Ko, Jeong Hoon et al.

Source: International Journal of Precision Engineering & Manufacturing-Green Technology; Jul2025, Vol. 12 Issue 4, p1091-1116, 26p

Dynamic Relevance-Weighting-Based Width-Adaptive Auto-Encoder.

Authors: Almejalli, Malak Bchir, Ouiem Ben Ismail, Mohamed Maher

Source: Applied Sciences (2076-3417); Jun2025, Vol. 15 Issue 12, p6455, 32p

Subject Terms: COST functions, AUTOENCODERS, DEEP learning, DYNAMIC models, ORIGINALITY

Data-Driven Method for Predicting Remaining Useful Life of Bearings Based on Multi-Layer Perception Neural Network and Bidirectional Long Short-Term Memory Network.

Authors: Tai, Yongfeng Yan, Xingyu Geng, Xiangyi et al.

Source: Structural Durability & Health Monitoring (SDHM); 2025, Vol. 19 Issue 2, p365-383, 19p

Subject Terms: LONG short-term memory, REMAINING useful life, PARTICLE swarm optimization, PRINCIPAL components analysis, ROLLER bearings, ACCELERATED life testing

MCBA-MVACGAN: A Novel Fault Diagnosis Method for Rotating Machinery Under Small Sample Conditions.

Authors: Huang, Wenhan Zhang, Xiangfeng Jiang, Hong et al.

Source: Machines; Jan2025, Vol. 13 Issue 1, p71, 25p

Subject Terms: GENERATIVE adversarial networks, FAULT diagnosis, DIAGNOSIS, PROBLEM solving, DATA modeling

Intelligent Fault Diagnosis Method Based on Neural Network Compression for Rolling Bearings.

Authors: Wang, Xinren Hu, Dongming Fan, Xueqi et al.

Source: Symmetry (20738994); Nov2024, Vol. 16 Issue 11, p1461, 19p

Subject Terms: FAULT diagnosis, CONVOLUTIONAL neural networks, INTELLIGENT networks, INDUSTRIAL equipment, ROLLER bearings, DIAGNOSIS

Control stability analysis of dynamic model with time delay for quadrotor UAV.

Authors: Li, Xi Qi, Guoyuan Zhang, Limin

Source: Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering; Oct2024, Vol. 238 Issue 13, p1269-1282, 14p

Subject Terms: ANGULAR velocity, STABILITY criterion, VALUE engineering, DYNAMIC stability, DYNAMIC models, ARTIFICIAL satellite attitude control systems

Intelligent fault diagnosis of machinery based on hybrid deep learning with multi temporal correlation feature fusion.

Authors: Lv, Yaqiong Zhang, Xiaohu Cheng, Yiwei et al.

Source: Quality & Reliability Engineering International; Oct2024, Vol. 40 Issue 6, p3517-3536, 20p

Subject Terms: ARTIFICIAL neural networks, CONVOLUTIONAL neural networks, FAULT diagnosis, COMPARATIVE method, FEATURE extraction

Development of an acoustic fault diagnosis system for UAV propeller blades.

Authors: Steinhoff, Leon Koschlik, Ann-Kathrin Arts, Emy et al.

Source: CEAS Aeronautical Journal; Oct2024, Vol. 15 Issue 4, p881-893, 13p

Ultrasonic guided Wave Signal Denoising Method Based on one-dimensional convolution and Full connection Model Fusion Denoising autoencoder.

Authors: Yang, Yingfeng Qiu, Guangwen Lin, Yizhou et al.

Source: Journal of Physics: Conference Series; 2024, Vol. 2822 Issue 1, p1-12, 12p

UAV propeller fault diagnosis using deep learning of non-traditional χ²-selected Taguchi method-tested Lempel–Ziv complexity and Teager–Kaiser energy features.

Authors: Al-Haddad, Luttfi A. Giernacki, Wojciech Basem, Ali et al.

Source: Scientific Reports; 8/10/2024, Vol. 14 Issue 1, p1-16, 16p