Chaotic chimp-mountain gazelle optimized FOPID control for frequency regulation in islanded airport microgrids with heterogeneous energy systems by Odelu P., Chandan Kumar Shiva, Sachidananda Sen, Vedik Basetti, Chandra Sekhar Reddy

“…Simulation results demonstrates that the CCMGO optimized fractional order proportional-integral-derivative controller exhibits better performances compared to the conventional genetic algorithm and particle swarm optimization based controllers, as well as contemporary metaheuristic algorithms like grey wolf optimizer and whale optimization algorithm. …”
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Maneuver Strategy for Active Spacecraft to Avoid Space Debris and Return to the Original Orbit by Qun Fang, Zhen Zhang, Haodong Meng, Xiaolong Wang, Xiuwei Zhang

“…It has modified the artificial potential field (APF) method and particle swarm optimization algorithm, with an aim to help spacecraft avoid the space debris group and return to the original orbit. …”
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Optimization of the heat recovery performance of enhanced geothermal system based on PSO-GA-BP neural networks and analytic hierarchy process by Ling Zhou, Jingchao Sun, Yanjun Zhang, Yunjuan Chen, Honglei Lei

“…Based on the numerical simulation data, optimized Back-Propagation Neural Network (BPNN) prediction models combining the Particle Swarm Optimization (PSO) and the Genetic Algorithm (GA) were developed to investigate the impact of various factors on the heat recovery performance of a three-horizontal-well EGS in the Zhacang geothermal field. …”
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An Enhanced Distribution System Performance with Optimization Techniques for Location of Electrical Vehicle Charging Stations by Sainadh Singh Kshatri, Venkata Anjani Kumar G, Chilakapati Lenin Babu, Palepu Suresh Babu

“…The GWO algorithm's performance is evaluated in comparison to that of the prevalent Particle Swarm Optimization (PSO) methodology. …”
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Optimizing ensemble learning for satellite-based multi-hazard monitoring and susceptibility assessment of landslides, land subsidence, floods, and wildfires by Seyed Vahid Razavi-Termeh, Abolghasem Sadeghi-Niaraki, Farman Ali, Biswajeet Pradhan, Soo-Mi Choi

“…To address this gap, this study uses two meta-heuristic algorithms (Genetic Algorithm (GA) and Particle Swarm Optimization (PSO)) to provide an optimized Random Forest (RF) model with better predictive ability. …”
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Adaptive Hybrid PSO-Embedded GA for neuroevolutionary training of multilayer perceptron controllers in VSC-based islanded microgrids by Yared Bekele Beyene, Getachew Biru Worku, Lina Bertling Tjernberg

“…This paper introduces a novel hybrid optimization algorithm, Adaptive Hybrid PSO-Embedded GA (AHPEGA), which dynamically adapts to optimization performance by integrating Particle Swarm Optimization (PSO) and Genetic Algorithms (GA). …”
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A multistate transition model for survival estimation in randomized trials with treatment switching and a cured subgroup by Haixia Hu, Ling Wang, Kejian Wu, Wei Ge, Jielai Xia, Chen Li

“…The particle swarm optimization algorithm is employed to estimate the model parameters. …”
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Cost-optimal sizing of battery energy storage systems in microgrids using artificial Rabbits optimization by Riwa Q. Momani, Ahmad Abuelrub, Hussein M.K. Al-Masri, Ali Q. Al-Shetwi

“…ARO is benchmarked against Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC), and Firefly Algorithm (FA). …”
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Enhancing grid connected wind energy conversion systems through fuzzy logic control optimization with PSO and GA techniques by Abdelhalim Borni, Noureddine Bessous, Layachi Zaghba, Abdelhak Bouchakour, Melkamu Sisay Agmas, Enas Ali, Sherif S. M. Ghoneim, Ayman Hoballah

“…Subsequently, the efficacy of fuzzy logic control without optimization is evaluated. Following this, FLC is enhanced by integrating particle swarm optimization and genetic algorithms. …”
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Lithium-Ion Battery State-of-Health Estimation Method Using Isobaric Energy Analysis and PSO-LSTM by Shaishai Zhao, Laijin Luo, Shanhe Jiang, Chaolong Zhang

“…In this regard, the improved LSTM NN refers to the selection of the number of hidden layers and the learning rate of the LSTM NN using the particle swarm algorithm (PSO). To verify the precision of the proposed method, validation experiments are performed based on four battery aging data with different charging multipliers. …”
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A novel approach for predicting the standardised precipitation index considering climatic factors by Mustafa A. Alawsi, Salah L. Zubaidi, Laith B. Al-badranee

“…., tolerance technique), in addition to, artificial neural network (ANN) combined with particle swarm optimisation (PSO)). The data on climatic factors were applied to build and evaluate the SPI 3 model from 1990 to 2020 for the Al-Kut region. …”
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Optimized CNN-LSTM with hybrid metaheuristic approaches for solar radiation forecasting by İrem Fatma Şener, İhsan Tuğal

“…The performance of several machine learning and deep learning models, including Long Short-Term Memory, Autoregressive Integrated Moving Average, Multilayer Perceptron, Random Forest, XGBoost, Support Vector Regression, and a hybrid CNN-LSTM model, is evaluated for daily solar radiation forecasting. To improve the accuracy of the model, hyperparameter optimization is applied to the CNN-LSTM model using three metaheuristic algorithms: Particle Swarm Optimization, Grey Wolf Optimization, and Starfish Optimization Algorithm. …”
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Resilient VPP cost optimization in DER-driven microgrids for large distribution systems considering uncertainty during extreme events by T.D. Suresh, M. Thirumalai, R. Hemalatha, Mohit Bajaj, Vojtech Blazek, Lukas Prokop

“…Simulation results demonstrate the BWO-based strategy’s superior performance, reducing total objective cost to $2.54 million, outperforming genetic algorithm (GA) and particle swarm optimization (PSO) by 5.01% and 8.54% respectively. …”
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Hyperparameters optimization of evolving spiking neural network using artificial bee colony for unsupervised anomaly detection by Rehan Rabie, Sahran Shahnorbanun, Alyasseri Zaid Abdi Alkareem, Sani Nor Samsiah, Al-Betar Mohammed Azmi

“…Further validation was provided by comparing the proposed OeSNN-ABC against five well-known optimization algorithms: particle swarm optimization, grey wolf optimization, flower pollination algorithm, whale optimization algorithm, and grid search, alongside other classifiers such as random forest, support vector machine, and k-nearest neighbor. …”
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State of charge estimation of lithium-ion batteries in an electric vehicle using hybrid metaheuristic - deep neural networks models by Zuriani Mustaffa, Mohd Herwan Sulaiman, Jeremiah Isuwa

“…These include the barnacle mating optimizer-deep neural networks (BMO-DNNs) with an MAE of 5.3848, an RMSE of 7.0395, and a convergence value of 0.0492; the evolutionary mating algorithm-deep neural networks (EMA-DNNs) with an MAE of 7.6127, an RMSE of 11.2287, and a convergence value of 0.0536; and the particle swarm optimization-deep neural networks (PSO-DNNs) with an MAE of 4.3089, an RMSE of 5.9672, and a convergence value of 0.0345. …”
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IoT-enabled real-time health monitoring system for adolescent physical rehabilitation by Jie Yang, Juanjuan Hu, Wenrui Chen

“…Advanced signal processing and filtering techniques are employed to minimize noise interference and improve data accuracy. A particle swarm optimization support vector machine (PSO-SVM) algorithm is utilized to classify motion patterns. …”
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Indirect Determination Approach of Blast-Induced Ground Vibration Based on a Hybrid SSA-Optimized GP-Based Technique by Zhaoxin Jiang, Hongyan Xu, Hui Chen, Bei Gao, Shijie Jia, Zhi Yu, Jian Zhou

“…The accurate determination of blast-induced ground vibration has an important significance in protecting human activities and the surrounding environment. For evaluating the peak particle velocity resulting from the quarry blast, a robust artificial intelligence system combined with the salp swarm algorithm (SSA) and Gaussian process (GP) was proposed, and the SSA was used to find the optimal hyperparameters of the GP here. …”
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Research on Ship Heave Motion Compensation Control Under Complex Sea State Environment Based on Improved Reinforcement Learning by ZHANG Qin, ZHOU Jingyi, WANG Xingyue, HU Xiong

“…This algorithm surpasses step control methods optimized through particle swarm optimization and outperforms traditional TD3 reinforcement learning methodologies. …”
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Augmented robustness in home demand prediction: Integrating statistical loss function with enhanced cross-validation in machine learning hyperparameter optimisation by Banafshe Parizad, Ali Jamali, Hamid Khayyam

“…Using three evolutionary algorithms Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Differential Evolution (DE) we optimize two ensemble models: XGBoost and LightGBM. …”
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Medium- Long-Term Runoff Forecasting Using Interpretable Hybrid Machine Learning Model for Data-Scarce Regions by YOU Yu-jun, BAI Yun-gang, LU Zhen-lin, ZHANG Jiang-hui, CAO Biao, LI Wen-zhong, YU Qi-ying

“…[Methods] Based on historical precipitation, temperature, and runoff sequences from the Yulongkashi River, a Convolutional Neural Network-Bidirectional Gated Recurrent Unit-Attention (CNN-BiGRU-Attention) model was developed. An Improved Particle Swarm Optimization (IPSO) algorithm was used to optimize this model, forming the IPSO-CNN-BiGRU-Attention hybrid model. …”
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