Optimized Support Vector Machine Assisted BOTDA for Temperature Extraction With Accuracy Enhancement by Hongna Zhu, Lei Yu, Yufeng Zhang, Le Cheng, Zhenyu Zhu, Jiayin Song, Jinli Zhang, Bin Luo, Kai Yang

“…Three typical intelligent optimization algorithms, particle swarm optimization algorithm, genetic algorithm and firefly algorithm are explored to optimize the SVM parameters. …”
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Hermetically sealed ecodesign distribution transformer weight optimization considering power losses and total ownership cost (TOC) by Mohammad Hassan Hashemi, Ulas Kilic

“…Specifically, the study employs Differential Evolution (DE), Particle Swarm Optimization (PSO), and Grey Wolf Optimization (GWO) algorithms to compare their efficacy against conventional design approaches. …”
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Optimized integration of photovoltaic systems and distribution static compensators in distribution networks using a novel discrete-continuous version of the adaptive JAYA algorithm... by Paolo Iván Cubillo-Leyton, Oscar Danilo Montoya, Luis Fernando Grisales-Noreña

“…For comparison, the discrete-continuous versions of the vortex search algorithm (VSA), the sine-cosine algorithm (SCA), Phasor Particle Swarm Optimization (PPSO), New Self-Organising Hierarchical PSO (NHPSO-JTVAC), Differential Evolution (DE), Gold Search Optimization (GSO) and the classical version of JAYA are used, validating the effectiveness of our proposal on the 33- and 69-bus test systems while considering variable generation and demand. …”
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A Hybrid Machine Learning Framework for Early Fault Detection in Power Transformers Using PSO and DMO Algorithms by Mohammed Alenezi, Fatih Anayi, Michael Packianather, Mokhtar Shouran

“…This study introduces a novel machine learning framework that integrates Particle Swarm Optimization (PSO) and Dwarf Mongoose Optimization (DMO) algorithms for feature selection and hyperparameter tuning, combined with advanced classifiers such as Decision Trees (DT), Random Forests (RF), and Support Vector Machines (SVM). …”
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Performance Analysis of Fractionalized Order PID Controller-based on Metaheuristic Optimisation Algorithms for Vehicle Cruise Control Systems by Abdelhakim Idir, Abderrahim Zemmit, Khatir Khettab, Mokhtar Nesri, Sifelislam Guedida, Laurent Canale

“…A comparative analysis is conducted between classical PID controllers and FrOPID controllers optimized using three metaheuristic algorithms: Harris Hawks Optimization (HHO), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO). …”
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Research on the Transformer Failure Diagnosis Method Based on Fluorescence Spectroscopy Analysis and SBOA Optimized BPNN by Xueqing Chen, Dacheng Li, Anjing Wang

“…Based on various preprocessed and dimensionally reduced data, transformer failure diagnosis models based on the particle swarm optimization algorithm (PSO) and the secretary bird optimization algorithm (SBOA) optimized BPNN are established to quantitatively analyze the state of insulating oil and predict the durations of transformer failure. …”
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SCUC Considering Loads and Wind Power Forecasting Uncertainties using Binary Gray Wolf Optimization Method by Majid Moazzami, Sayed Jamal Al-Din Hosseini, Hossein Shahinzadeh, Gevork B. Gharehpetian, Jalal Moradi

“…Ultimately, the unit commitment schedule and optimal generation of each unit are determined and the optimization results are compared with the solution of genetic algorithm and particle swarm algorithm.…”
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Development and Fuel Economy Optimization of Series–Parallel Hybrid Powertrain for Van-Style VW Crafter Vehicle by Ahmed Nabil Farouk Abdelbaky, Aminu Babangida, Abdullahi Bala Kunya, Péter Tamás Szemes

“…A MATLAB (R2024b) Simulink model of the hybrid system is developed, and its speed tracking PID controller is optimized using genetic algorithm (GA) and particle swarm optimization (PSO) methods. …”
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Innovative real data-driven multi-objective optimization for sustainable energy in Siwa Oasis, Egypt using HYCHOPSO by Hosam Abdelhadi, Ahmed Mohamed Mahmoud, Ebtisam Mostafa Mohamed Saied, Mohamed Ahmed Ebrahim

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Cost Optimization of AC Microgrids in Grid-Connected and Isolated Modes Using a Population-Based Genetic Algorithm for Energy Management of Distributed Wind Turbines by Luis Fernando Grisales-Noreña, Héctor Pinto Vega, Oscar Danilo Montoya, Vanessa Botero-Gómez, Daniel Sanin-Villa

“…This research investigates the effectiveness of four metaheuristic algorithms, the Population-Based Genetic Algorithm, Particle Swarm Optimization, JAYA, and Generalized Normal Distribution Optimizer, for managing the energy production of wind-based distributed generators (DGs). …”
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Optimal Multi-Objective Reconfiguration in distribution systems using the Novel Intelligent Water Drops approach by Hajar Bagheri Tolabi, Mohd Hasan Ali

“…The obtained results prove the proposed technique is more accurate than other well known methods such as Genetic Algorithm, Particle Swarm Optimization, and Harmony Search algorithm meanwhile it has an efficient convergence property in compared with other intelligent search algorithms. …”
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A high-speed MPPT based horse herd optimization algorithm with dynamic linear active disturbance rejection control for PV battery charging system by AL-Wesabi Ibrahim, Jiazhu Xu, Imad Aboudrar, Khaled Alwesabi, Li danhu, Hassan Z. Al Garni, Elhachemi Mammeri, Hossam Kotb, Mohit Bajaj, Shir Ahmad Dost Mohammadi

“…Then, in comparison to the traditional method (perturb & observe; P&O) and metaheuristic algorithms (conventional particle swarm optimization; CPSO, grasshopper optimization; GHO, and deterministic PSO; DPSO) through DSEC, the simulations results demonstrate that the combination HHOA-LADRC can successfully track the global maximum peak (GMP) with less fluctuations and a quicker convergence time. …”
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Optimal energy management of distributed generation resources in a microgrid under various load and solar irradiance conditions using the artificial bee colony algorithm by Tareq Hamadneh, Omar Alsayyed, Belal Batiha, El Manaa Barhoumi, Mehrdad Ahmadi Kamarposhti, Hassan Haghighi, Phatiphat Thounthong, Ilhami Colak

“…The results demonstrate that the proposed algorithm consistently achieves superior performance in minimizing the total operation cost compared to traditional bio-inspired optimization techniques such as genetic algorithms, particle swarm optimization, and a modified bat algorithm. …”
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Opposition-based learning techniques in metaheuristics: classification, comparison, and convergence analysis by Rihab Lakbichi, Farouq Zitouni, Saad Harous, Aridj Ferhat, Abdelhadi Limane, Abdulaziz S. Almazyad, Guojiang Xiong, Ali Wagdy Mohamed

“…To systematically assess the effectiveness of these techniques, five widely used OBL variants—basic opposition-based learning, quasi-opposition-based learning, generalized opposition-based learning, current optimum opposition-based learning, quasi-reflection opposition-based learning—were selected for implementation within five well-established MAs: differential evolution, genetic algorithm, particle swarm optimization, artificial bee colony, and harmony search. …”
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Optimizing Load Frequency Control of Multi-Area Power Renewable and Thermal Systems Using Advanced Proportional–Integral–Derivative Controllers and Catch Fish Algorithm by Saleh A. Alnefaie, Abdulaziz Alkuhayli, Abdullah M. Al-Shaalan

“…The performance of LFC with CFA-tuned PID, PI, cascaded PI(PDN), and FOPID, PI(1+DD) controllers is compared to other optimization techniques, including sine cosine algorithm (SCA), particle swarm optimization (PSO), brown bear algorithm (BBA), and grey wolf optimization (GWO), in a two-area power system combined with RESs under various conditions. …”
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Inversion of Water Quality Parameters from UAV Hyperspectral Data Based on Intelligent Algorithm Optimized Backpropagation Neural Networks of a Small Rural River by Manqi Wang, Caili Zhou, Jiaqi Shi, Fei Lin, Yucheng Li, Yimin Hu, Xuesheng Zhang

“…Again, based on the screened features, a back-propagation neural network (BPNN) model optimized using a mixture of the genetic algorithm (GA) and the particle swarm optimization (PSO) algorithm was established as a means of estimating water quality parameter concentrations. …”
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Improving aquifer vulnerability assessment and its explainability in the Zanjan aquifer: Integrating DRASTIC model and optimized long short-term memory-based metaheuristic algorith... by Mojgan Bordbar, Khabat Khosravi, Changhyun Jun, Dongkyun Kim, Sayed M Bateni, Mahmood Safarzadeh, Hamid Kardan Moghaddam, Shohreh Azizi

“…The LSTM model was optimized using the particle swarm optimizer (PSO) and equilibrium optimizer (EO) metaheuristic algorithms. …”
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Optimal Structure to Maximize Torque per Volume for the Consequent-Pole PMSM and Investigating the Temperature Effect by Alireza Hosseinpour, Ahmed Abbas, Mahmoud Oukati Sadegh, Atif Iqbal, Aymen Flah, Lukas Prokop, Enas Ali, Ramy N. R. Ghaly

“…Therefore, to maximize the torque/volume ratio, four metaheuristic optimization algorithms, including Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Differential Evolution (DE), and Teaching Learn Base Optimization (TLBO), have been implemented, and the mentioned index is optimized. …”
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Multi-Criteria Optimization of a Standalone Photovoltaic System in Cyprus (Techno-Economic Analysis) by Athina Vogiatzoglou, Konstantinos Alexakis, Dimitris Askounis

“…This study proposes a two-stage optimization approach for standalone photovoltaic systems, employing three distinct optimization algorithms—NSGA-II, DEMO, and Particle Swarm Optimization—to minimize both the Loss of Load Probability (LLP) and the life cycle cost (LCC). …”
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High-Resolution Direction of Arrival Estimation of Underwater Multitargets Using Swarming Intelligence of Flower Pollination Heuristics by Nauman Ahmed, Huigang Wang, Shanshan Tu, Norah A.M. Alsaif, Muhammad Asif Zahoor Raja, Muhammad Kashif, Ammar Armghan, Yasser S. Abdalla, Wasiq Ali, Farman Ali

“…The measuring parameters like robustness against noise and element quantity, estimation accuracy, computation complexity, various numbers of hydrophones, variability analysis, frequency distribution and cumulative distribution function of root mean square error (RMSE), and resolution ability are applied for analyzing the performance of the proposed model with additive white Gaussian noise (AWGN). For this purpose, particle swarm optimization (PSO), minimum variance distortion-less response (MVDR), multiple signal classification (MUSIC), and estimation of signal parameter via rotational invariance technique (ESPRIT) standard counterparts are employed along with Crammer–Rao bound (CRB) to improve the worth of the proposed setup further. …”
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