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Teaching–learning-based optimization algorithm: analysis study and its application
Published 2024“…The teaching–learning-based optimization (TLBO) algorithm is a novel nature-based optimization approach that has attracted a lot of interest from researchers because of its great capacity to handle optimization problems. …”
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Multi-Objective Optimisation of Injection Moulding Process for Dashboard Using Genetic Algorithm and Type-2 Fuzzy Neural Network
Published 2024“…<p dir="ltr">This study examines the use of injection moulding to evaluate mechanical properties in plastic products, such as shear and residual stresses. …”
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Augmented arithmetic optimization algorithm using opposite-based learning and lévy flight distribution for global optimization and data clustering
Published 2022“…This paper proposes a new data clustering method using the advantages of metaheuristic (MH) optimization algorithms. A novel MH optimization algorithm, called arithmetic optimization algorithm (AOA), was proposed to address complex optimization tasks. …”
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Monitoring Bone Density Using Microwave Tomography of Human Legs: A Numerical Feasibility Study
Published 2021“…This study was performed using an in-house finite-element method contrast source inversion algorithm (FEM-CSI). …”
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Extended Behavioral Modeling of FET and Lattice-Mismatched HEMT Devices
Published 2016Get full text
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Day-Ahead Load Demand Forecasting in Urban Community Cluster Microgrids Using Machine Learning Methods
Published 2022“…Thus, to identify the best load forecasting method in cluster microgrids, this article implements a variety of machine learning algorithms, including linear regression (quadratic), support vector machines, long short-term memory, and artificial neural networks (ANN) to forecast the load demand in the short term. …”
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Artificial neural network algorithms. (c1999)
Published 1999Get full text
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Image-Based Air Quality Estimation Using Convolutional Neural Network Optimized by Genetic Algorithms: A Multi-Dataset Approach
Published 2025“…The convolutional neural network is optimized using genetic algorithms, which dynamically tune hyper-parameters such as learning rate, batch size, and momentum to improve performance and generalizability across diverse environmental conditions. …”
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A Clinically Interpretable Approach for Early Detection of Autism Using Machine Learning With Explainable AI
Published 2025“…While research in ASD diagnosis is evolving through the application of machine learning (ML) techniques, practical implementation in clinical settings has not progressed at the same pace. …”
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Metaheuristic Optimization Algorithms for Training Artificial Neural Networks
Published 2012“…The Cuckoo Search (CS) algorithm is a recently developed meta-heuristic optimization algorithm which is suitable for solving optimization problems. …”
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Distributed DRL-Based Downlink Power Allocation for Hybrid RF/VLC Networks
Published 2021“…We implement a simulation environment to benchmark the proposed distributed DRL-based method against other methods such as Q-Learning (QL) and Deep Q-Networks (DQN), and centralized heuristic power allocation algorithms. …”
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A reduced model for phase-change problems with radiation using simplified PN approximations
Published 2025“…To solve the coupled equations, we implement a second-order implicit scheme for the time integration and a mixed finite element method for the space discretization. A Newton-based algorithm is also adopted for solving the nonlinear systems resulting from the considered monolithic approach. …”
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A Novel BIPV Reconfiguration Algorithm for Maximum Power Generation under Partial Shading
Published 2020“…The system is optimised for maximum yield to determine the optimal configuration and number of modules for each string using a genetic algorithm. The outcomes from the algorithm are based on clustering the solar insolation values and then applying a genetic algorithm optimisation to indicate the optimum BIPV array layout for maximum yield.…”