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data algorithm » jaya algorithm (Expand Search), deer algorithm (Expand Search)
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Automatic Detection of High Temperature Hydrogen Attack Defects from Ultrasonic A-scan Signals.
Published 2020“…In this paper, an out-of-service pressure vessel known to have lots of high temperature hydrogen attach (HTHA) defects is used to develop in a cost effective manner a database of ultrasonic A-scan signals. …”
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Convergence of Photovoltaic Power Forecasting and Deep Learning: State-of-Art Review
Published 2021“…These technologies include federated learning, deep transfer learning, incremental learning, and big data DL. …”
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Real-Time Performance Evaluation of a Genetic Algorithm Based Fuzzy Logic Controller for IPM Motor Drives
Published 2005“…The proposed GFLC is developed to have less computational burden, which makes it suitable for real-time implementation. …”
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Thermodynamic Analysis and Optimization of Densely-Packed Receiver Assembly Components in High-Concentration CPVT Solar Collectors
Published 2016“…In this study, detailed design models and simulation algorithms of three state-of-the-art components commonly incorporated into the densely-packed receiver assemblies of high-concentration CPVT solar collectors are presented. …”
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Hybrid deep learning based threat intelligence framework for Industrial IoT systems
Published 2025“…The proposed approach was also compared against several contemporary deep learning-based architectures and existing benchmark algorithms. …”
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Deep and transfer learning for building occupancy detection: A review and comparative analysis
Published 2022“…The article’s primary emphasis is on reviewing deep learning (DL), and transfer learning (TL) approaches for occupancy detection. …”
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Distributed Tree-Based Machine Learning for Short-Term Load Forecasting With Apache Spark
Published 2021“…<p>Machine learning algorithms have been intensively applied to perform load forecasting to obtain better accuracies as compared to traditional statistical methods. …”
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Nonlinear analysis of shell structures using image processing and machine learning
Published 2023“…The proposed approach can be significantly more efficient than training a machine learning algorithm using the raw numerical data. To evaluate the proposed method, two different structures are assessed where the training data is created using nonlinear finite element analysis. …”
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Development of Machine Learning Models for Studying the Premixed Turbulent Combustion of Gas-To-Liquids (GTL) Fuel Blends
Published 2024“…In addition, the possible minimum and maximum values of responses at the corresponding operating parameters are found using a genetic algorithm (GA) approach. Model 1 could capture the computational fluid dynamics (CFD) outputs with high precision at different flame radiuses and time instants with a maximum absolute error percentage of 5.46%. …”
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Learning Spatiotemporal Latent Factors of Traffic via Regularized Tensor Factorization: Imputing Missing Values and Forecasting
Published 2019“…We propose a tensor representation for the series of road network snapshots, and develop a regularized factorization method to estimate the missing values, while learning the latent factors of the network. …”
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Reinforcement Learning for Resilient Aerial-IRS Assisted Wireless Communications Networks in the Presence of Multiple Jammers
Published 2024“…<p dir="ltr">The evolving landscape of beyond 5G and 6G wireless communication systems in smart urban environments faces numerous interference-related challenges posed by legitimate and illicit devices. …”
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Privacy-preserving energy optimization via multi-stage federated learning for micro-moment recommendations
Published 2025“…A comparative evaluation of three FL algorithms (FedAvg, FedProx, Mime-lite) identifies the most suitable aggregation strategy. …”
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