Výsledky vyhledávání - Stacked sparse autoencoder data reconstruction*

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

Latent Feature‐Based Type 2 Diabetes Prediction Using a Hybrid Stacked Sparse Autoencoder and Machine Learning Models.

Autoři: Abdussamad Daud, Hanita Sokkalingam, Rajalingam a další

Zdroj: Engineering Reports; Sep2025, Vol. 7 Issue 9, p1-17, 17p

Témata: TYPE 2 diabetes, MACHINE learning, CLINICAL decision support systems, METADATA, FORECASTING, FEATURE extraction

Early identification of out-of-roundness damage wheels in railway freight vehicles using a wayside system and a stacked sparse autoencoder.

Autoři: Jorge, T. Magalhães, J. Silva, R. a další

Zdroj: Vehicle System Dynamics; Feb2025, Vol. 63 Issue 2, p232-257, 26p

Témata: FEATURE extraction, RAILROAD trains, AUTOENCODERS, ARTIFICIAL intelligence, MULTISENSOR data fusion, ROLLING stock

An Innovative Study for Tool Wear Prediction Based on Stacked Sparse Autoencoder and Ensemble Learning Strategy.

Autoři: He, Zhaopeng Shi, Tielin Chen, Xu

Zdroj: Sensors (14248220); Apr2025, Vol. 25 Issue 8, p2391, 14p

Témata: ARTIFICIAL neural networks, MACHINE learning, ENSEMBLE learning, NUMERICAL control of machine tools, AUTOENCODERS, DEEP learning

Multimode system condition monitoring using sparsity reconstruction for quality control

Autoři: Wafa Bougheloum Mounir Bekaik Sofiane Gherbi

Témata: Diagnosis, Process monitoring multivariate statistical process control, Stacked sparse autoencoder data reconstruction

Relation: https://zenodo.org/records/7827354; oai:zenodo.org:7827354

Dostupnost: https://doi.org/10.11591/ijece.v13i3.pp2711-2720
https://zenodo.org/records/7827354

Lithium exploration targeting through robust variable selection and deep anomaly detection: An integrated application of sparse principal component analysis and stacked autoencoders.

Autoři: Esmaeiloghli, Saeid Lima, Alexandre Sadeghi, Behnam

Zdroj: Geochemistry / Chemie der Erde. Nov2024, Vol. 84 Issue 4, pN.PAG-N.PAG. 1p.

Témata: Principal components analysis, Renewable energy sources, Employee reviews, Signal reconstruction, Metal industry

Intelligent evaluation method for identifying favorable shale oil areas based on improved stacked sparse autoencoder.

Autoři: Rui Xu Tie Yan Shihui Sun a další

Zdroj: Oil Shale; 2025, Vol. 42 Issue 1, p79-114, 36p

Témata: SHALE oils, SUPERVISED learning, PETROLEUM prospecting, AUTOENCODERS, MACHINE learning

Improved stacked sparse auto encoder by adaptive shuffled shepherd optimization algorithm for ERT image reconstruction

Autoři: Sathesh Ammaiappan Guanghui Liang Feng Dong

Zdroj: Measurement Science and Technology. 36:065406

RETRACTED: Optimization using Internet of Agent based Stacked Sparse Autoencoder Model for Heart Disease Prediction.

Autoři: Baviskar, Vaishali Verma, Madhushi Chatterjee, Pradeep a další

Zdroj: Expert Systems; Dec2024, Vol. 41 Issue 12, p1-20, 20p

Témata: CONVOLUTIONAL neural networks, MACHINE learning, OPTIMIZATION algorithms, NOSOLOGY, CLASSIFICATION algorithms

Visual Motion Segmentation in Crowd Videos Based on Spatial-Angular Stacked Sparse Autoencoders.

Autoři: Hafeezallah, Adel Al-Dhamari, Ahlam Abu-Bakar, Syed Abd Rahman

Zdroj: Computer Systems Science & Engineering; 2023, Vol. 47 Issue 1, p593-611, 19p

Témata: COLLECTIVE behavior, IMAGE segmentation, DEEP learning, DATA analysis, ACCURACY

Web-S4AE: a semi-supervised stacked sparse autoencoder model for web robot detection.

Autoři: Jagat, Rikhi Ram Sisodia, Dilip Singh Singh, Pradeep

Zdroj: Neural Computing & Applications; Aug2023, Vol. 35 Issue 24, p17883-17898, 16p

Témata: BLOGS, ROBOTS, DEEP learning, COMPUTER software, RANDOM forest algorithms, DECISION trees, SUPERVISED learning

Hyperband Tuned Deep Neural Network With Well Posed Stacked Sparse AutoEncoder for Detection of DDoS Attacks in Cloud

Autoři: Aanshi Bhardwaj Veenu Mangat Renu Vig

Zdroj: IEEE Access, Vol 8, Pp 181916-181929 (2020)

Témata: distributed denial of service attack, intrusion detection, Machine learning, cloud computing, 0202 electrical engineering, electronic engineering, information engineering, Electrical engineering. Electronics. Nuclear engineering, 02 engineering and technology, artificial neural network, TK1-9971

Přístupová URL adresa: https://doaj.org/article/37ba09dfdb5841b7a8e095ef9657e1f6

Reconstruction-based stacked sparse auto-encoder for nonlinear industrial process fault diagnosis.

Autoři: Qihang Weng Shaojun Ren Baoyu Zhu a další

Zdroj: Maintenance & Reliability / Eksploatacja i Niezawodność; 2024, Vol. 26 Issue 1, p1-16, 16p

Témata: MANUFACTURING processes, FAULT diagnosis, INDUSTRIALISM, NONLINEAR systems, DIAGNOSIS

Research on improving classification accuracy of cavitation intensity by sensor fusion.

Autoři: Kang, Ziyang Zhou, Jiayu Wang, Yandong a další

Zdroj: Sensor Review; 2025, Vol. 45 Issue 6, p846-856, 11p

Témata: MULTISENSOR data fusion, HYDRAULIC turbines, RANDOM forest algorithms, ACOUSTIC intensity, FEATURE extraction, CAVITATION, CLASSIFICATION

Fault Diagnosis for Power Batteries Based on a Stacked Sparse Autoencoder and a Convolutional Block Attention Capsule Network.

Autoři: Zhou, Juan Zhang, Shun Wang, Peng

Zdroj: Processes; Apr2024, Vol. 12 Issue 4, p816, 19p

Témata: CAPSULE neural networks, FAULT diagnosis, ELECTRIC vehicle batteries, ELECTRIC vehicles, ELECTRIC power failures, ELECTRIC fault location, FAILURE mode & effects analysis

A hybrid metaheuristic federated learning approach based attack detection system for multi-cloud environment.

Autoři: Verma, Rashmi Jailia, Manisha

Zdroj: Journal of Cloud Computing (2192-113X); 11/27/2025, Vol. 14 Issue 1, p1-22, 22p

Témata: FEDERATED learning, CLOUD computing, CLOUD computing security measures, INTRUSION detection systems (Computer security), DATA privacy, ANOMALY detection (Computer security), MACHINE learning, METAHEURISTIC algorithms

Stacked sparse autoencoders monitoring model based on fault-related variable selection.

Autoři: Yin, Jie Yan, Xuefeng

Zdroj: Soft Computing - A Fusion of Foundations, Methodologies & Applications; Mar2021, Vol. 25 Issue 5, p3531-3543, 13p

Témata: ELECTRONIC data processing, INFORMATION processing, CHEMICAL industry, ACQUISITION of data, DATA modeling, EUCLIDEAN distance

Optimization Strategy of a Stacked Autoencoder and Deep Belief Network in a Hyperspectral Remote-Sensing Image Classification Model.

Autoři: Dai, Xiaoai Cheng, Junying Guo, Shouheng a další

Zdroj: Discrete Dynamics in Nature & Society; 4/28/2023, p1-20, 20p

Témata: DEEP learning, IMAGE recognition (Computer vision), REMOTE-sensing images, BOLTZMANN machine, REMOTE sensing, FEATURE extraction, ELECTRONIC data processing

Artificial neural network technique for improving prediction of credit card default: A stacked sparse autoencoder approach.

Autoři: Ebiaredoh-Mienye, Sarah. A. Esenogho, E. Swart, Theo G.

Zdroj: International Journal of Electrical & Computer Engineering (2088-8708); Oct2021, Vol. 11 Issue 5, p4392-4402, 11p

Témata: ARTIFICIAL neural networks, DEFAULT (Finance), CREDIT cards, MACHINE learning, MACHINE performance

Pseudo Zernike Moment and Deep Stacked Sparse Autoencoder for COVID-19 Diagnosis.

Autoři: Yu-Dong Zhang Khan, Muhammad Attique Ziquan Zhu a další

Zdroj: Computers, Materials & Continua; 2021, Vol. 69 Issue 3, p3145-3162, 18p

Témata: COVID-19 testing, DEEP learning, DATA augmentation, SPECKLE interference, COMPUTER vision