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201
EEG channels selection for stroke patients rehabilitation using equilibrium optimizer
Published 2025-08-01“…This article addresses this problem by presenting an innovative optimization-based approach to the channel selection problem, employing a novel binary equilibrium optimizer (EO) as an optimization technique to identify the most relevant EEG channels. …”
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202
Bone scintigraphy based on deep learning model and modified growth optimizer
Published 2024-10-01“…In addition, the second phase is named feature selection, and it is dependent on the Arithmetic Optimization Algorithm (AOA) being used to improve the Growth Optimizer (GO). …”
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203
Improved PESA algorithm based on comentropy
Published 2013-11-01“…Aiming at the issue that the computational effort the complexity and the running time of PESA algorithm are increasing rapidly with the growth of the solutions set number, a comentropy-based PESA algorithm (C-PESA) by merg-ing the entropy value metric into PESA algorithm was proposed. …”
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204
GAAOA-Lévy: a hybrid metaheuristic for optimized multilevel thresholding in image segmentation
Published 2025-07-01“…However, multilevel thresholding, a widely used segmentation technique, suffers from high computational complexity due to the exhaustive search for optimal thresholds. This paper addresses this challenge by proposing a hybrid Genetic Algorithm-Archimedes Optimization Algorithm (GAAOA), further enhanced with a Lévy flight function (GAAOA-Lévy), to improve efficiency and accuracy in multilevel thresholding. …”
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205
Optimizing Trajectories for Rechargeable Agricultural Robots in Greenhouse Climatic Sensing Using Deep Reinforcement Learning with Proximal Policy Optimization Algorithm
Published 2025-06-01“…In this paper, we propose a method based on Deep Reinforcement Learning enriched with a Proximal Policy Optimization (PPO) algorithm for determining the best trajectory an agricultural robot must follow to balance the number of measurements and autonomy adequately. …”
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206
An Improved Multi-Objective Adaptive Human Learning Optimization Algorithm and Its Application in Optimizing Formulation Schemes for Rotary Hearth Furnaces
Published 2025-06-01“…An improved multi-objective adaptive human learning optimization algorithm (IMOAHLO) is proposed, which enhances local optimization through neighborhood search and an adaptive learning mechanism. …”
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207
An efficient metaheuristic optimization algorithm for optimal power extraction from PV systems under various weather and load-changing conditions
Published 2025-09-01“…To address these challenges, a new algorithm called horse herd optimization (HHO) has been applied to the maximum power point tracking (MPPT) controller. …”
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208
Comparative Study of White Shark Optimization and Combined Meta-Heuristic Algorithm for Enhanced MPPT in Photovoltaic Systems
Published 2025-04-01“…This paper proposes a novel hybrid metaheuristic algorithm (MHA) for maximum power point tracking (MPPT), integrating particle swarm optimization (PSO), the differential evolution algorithm (DEA), and the grey wolf optimizer (GWO). …”
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209
Application of GA-ACO Optimized BP Neural Network in Fault Diagnosis of Planetary Gearbox
Published 2021-03-01“…Comparing the performance of ACO-BP neural network algorithm and GA-ACO-BP algorithm, the results show that the convergence speed of ACO Optimized BP neural network is slow and the recognition accuracy is not high, while GA-ACO-BP algorithm can accurately and quickly diagnose and identify the fault of planetary gearbox.…”
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210
OPTIMAL LOSSES IN POWER DISTRIBUTION NETWORKS
Published 2014-10-01“…The developed structural algorithm of technical losses of electricity in network 0,38–10 kV allows evaluating actual and optimal network loading, to determine minimum and reserves of losses enhancement, but it can be realize only when loading of lines and transformers is low. …”
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211
A Hybrid Whale Optimization Approach for Fast-Convergence Global Optimization
Published 2025-06-01“…In this paper, we introduce the Levy Flight-enhanced Whale Optimization Algorithm with Tabu Search elements (LWOATS), an innovative hybrid optimization approach that enhances the standard Whale Optimization Algorithm (WOA) with advanced local search techniques and elite solution management to improve performance on global optimization problems. …”
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212
An improved dung beetle optimizer based on Padé approximation strategy for global optimization and feature selection
Published 2025-03-01“…Feature selection is a crucial data processing method used to reduce dataset dimensionality while preserving key information. In this paper, we proposed a multi-strategy enhanced dung beetle optimization algorithm (mDBO) that integrates multiple strategies to effectively address the feature selection problem. …”
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213
Boosting feature selection efficiency with IMVO: Integrating MVO and mutation-based local search algorithms
Published 2025-06-01“…In this research, we introduce the Improved Multi-Verse Optimizer (IMVO) algorithm, a novel feature selection method that integrates the Multi-Verse Optimizer (MVO) with local search algorithms (LSAs). …”
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214
Fuzzy Guiding of Roulette Selection in Evolutionary Algorithms
Published 2025-02-01“…The algorithm can be an effective tool in solving a wide range of optimization problems, for example, optimization of computer network infrastructure.…”
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215
Current-to-Best Crossover for Modified Jaya Algorithm
Published 2025-08-01“…The Jaya algorithm is a recently designed metaheuristics and has been verified for its good performance in solving various engineering and scientific optimization applications. …”
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216
Mixed Multi-Strategy Improved Aquila Optimizer and Its Application in Path Planning
Published 2024-12-01“…Traditional Aquila Optimizers, while effective, face limitations such as uneven population initialization, a tendency to get trapped in local optima, and slow convergence rates. …”
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217
Study on the probabilistic characteristics of forces in the support structure of heliostat array based on the DBO-BP algorithm
Published 2025-07-01“…Dung beetle optimization (DBO) algorithm is a metaheuristic algorithm mimicking dung beetle ball-rolling behavior, while Back propagation (BP) neural network is a feedforward artificial neural network trained via error backpropagation to adjust parameters. …”
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218
Investigation, Optimization of Energy Consumption and Yield Modeling of Two Paddy Cultivars with Genetic-Artificial Bee Colony Algorithm
Published 2025-06-01“…The results of the bee-genetic algorithm optimization revealed that the majority of the consumed resources could be effectively managed on the farm to closely match optimal conditions. …”
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219
Slope stability prediction under seismic loading based on the EO-LightGBM algorithm
Published 2025-07-01Get full text
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220
Ship Formation and Route Optimization Design Based on Improved PSO and D-P Algorithm
Published 2025-01-01“…Based on this, a ship formation model combining improved particle swarm optimization algorithm and a generative route optimization method based on improved Douglas-Peucker algorithm are proposed. …”
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