Modeling of strike drone missions for conducting wave attacks in conditions of enemy anti-drone actions by Oleg Fedorovich, Dmytro Krytskyi, Mikhail Lukhanin, Oleksandr Prokhorov, Yuliia Leshchenko

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Chiller power consumption forecasting for commercial building based on hybrid convolution neural networks-long short-term memory model with barnacles mating optimizer by Mohd Herwan Sulaiman, Zuriani Mustaffa

“…The study compares the proposed CNN-LSTM-BMO against other metaheuristic optimization algorithms, including Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and Differential Evolution (DE). …”
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Optimizing sustainable blended concrete mixes using deep learning and multi-objective optimization by Rupesh Kumar Tipu, Preeti Rathi, Kartik S. Pandya, Vijay R. Panchal

“…The Multi-Objective Particle Swarm Optimization (MOPSO) algorithm finds multiple optimal solutions which simultaneously optimize three competing objectives that include strength maximization and cost minimization and cement reduction. …”
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Redefining IoT networks for improving energy and memory efficiency through compressive sensing paradigm by S. Balamurali, M. Kathirvelu, SatheeshKumar Palanisamy, Ines Hilali Jaghdam

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A solution to the Single-School school bus routing problem considering accessibility and economy by Zizhan Jiang, Jiying Wang, Siyuan Huang, Hua Daniel Xu

“…In the second stage, we establish a mixed-integer linear programming (MILP) model for SSMR-SBRP, aiming to minimize the total travel distance. Heuristic algorithms, such as Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), and Floyd-Warshall, are employed to determine the initial solution, which includes the optimal number of buses and their preliminary routes. …”
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EWT多重分解与若干新型元启发式算法优化的多层感知器月径流预测 by CAI Liang, BAO Yanfei, CUI Dongwen

“…To improve the accuracy of monthly runoff time series prediction, enhance the performance of multi-layer perceptron (MLP), and compare and verify the optimization effects of four new metaheuristic algorithms on benchmarking functions and instance objective functions, including catch fish optimization algorithm (CFOA), flood algorithm (FLA), arctic puffin optimization (APO), educational competition optimization (ECO), and particle swarm optimization (PSO), an EWT^III-CFOA/FLA/APO/ECO/PSO-MLP prediction model was proposed. …”
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K-Nearest Neighbors hybrid method for maximum power point tracking under partial shading for photovoltaic power systems by Djamel Guessoum, Maen Takrouri, Mohammad Rabih, Maissa Farhat, Sufian A. Badawi

“…The proposed method has surpassed various optimization techniques for MPPT, including particle swarm optimization (PSO) and Cuckoo search (CS). …”
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Multicore PSO Operation for Maximum Power Point Tracking of a Distributed Photovoltaic System under Partially Shading Condition by Ru-Min Chao, Ahmad Nasirudin, I-Kai Wang, Po-Lung Chen

“…A modified particle swarm optimization (PSO) algorithm based on the suggested search-agent deployment, retracking condition, and multicore operation is proposed in order to continuously locate the global maximum power point for the PV system. …”
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A Self-Tuning Variable Universe Fuzzy PID Control Framework with Hybrid BAS-PSO-SA Optimization for Unmanned Surface Vehicles by Huixia Zhang, Zhao Zhao, Yuchen Wei, Yitong Liu, Wenyang Wu

“…In this study, a hybrid heading control framework for unmanned surface vehicles (USVs) is proposed, combining variable domain fuzzy Proportional–Integral–Derivative (VUF-PID) with an improved algorithmic Beetle Antennae Search–Particle Swarm Optimization–Simulated Annealing (BAS-PSO-SA) optimization to address the multi-objective control challenge. …”
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Adaptive Bacterial Foraging Optimization by Hanning Chen, Yunlong Zhu, Kunyuan Hu

“…The experiments compare the performance of two versions of ABFO with the original BFO, the standard particle swarm optimization (PSO) and a real-coded genetic algorithm (GA) on four widely-used benchmark functions. …”
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Performance of pelican optimizer for energy losses minimization via optimal photovoltaic systems in distribution feeders. by Zuhair Alaas, Ghareeb Moustafa, Hany Mansour

“…Additionally, the model's findings indicate that the proposed PO version performs comparably to the Differential Evolution (DE), Particle Swarm Optimization (PSO), and Satin bowerbird optimizer (SBO) algorithms.…”
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Optimization of classifier ensemble diversity by Leif E. Peterson

“… Ensemble diversity was investigated for 12 classifiers and 16 datasets using a generalization error and ambiguity decomposition of the model bias-variance relationship. Diversity was optimized using a genetic algorithm and particle swarm optimization. …”
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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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Optimization of Injection-Molding Process Parameters for Weight Control: Converting Optimization Problem to Classification Problem by Peng Zhao, Zhengyang Dong, Jianfeng Zhang, Yi Zhang, Mingyi Cao, Zhou Zhu, Hongwei Zhou, Jianzhong Fu

“…A support vector classifier (SVC) method is applied to construct a classification hyperplane in which the weight error is supposed to be zero. A particle swarm optimization (PSO) algorithm contributes to the tuning of the hyperparameters of the SVC model in order to minimize the error between the SVC prediction results and the experimental results. …”
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Hybrid Algorithms for Fuzzy Reverse Supply Chain Network Design by Z. H. Che, Tzu-An Chiang, Y. C. Kuo, Zhihua Cui

“…In consideration of capacity constraints, fuzzy defect ratio, and fuzzy transport loss ratio, this paper attempted to establish an optimized decision model for production planning and distribution of a multiphase, multiproduct reverse supply chain, which addresses defects returned to original manufacturers, and in addition, develops hybrid algorithms such as Particle Swarm Optimization-Genetic Algorithm (PSO-GA), Genetic Algorithm-Simulated Annealing (GA-SA), and Particle Swarm Optimization-Simulated Annealing (PSO-SA) for solving the optimized model. …”
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Application of Artificial Intelligence Computer Intelligent Heuristic Search Algorithm by Fanghai Gong

“…After 231 iterations of particle swarm optimization algorithm, the optimal value is 6.83650785e-001. …”
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Optimization of software project evaluation system by Li ding .

“…A new network topology design method is proposed, and a software project performance evaluation model based on fuzzy neural network is established. An improved particle swarm optimization algorithm is introduced to solve the problem of determining the connection weight coefficient of the evaluation model accurately and efficiently. …”
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Evolutionary Algorithms for Edge Server Placement in Vehicular Edge Computing by A. Surayya, Md Muzakkir Hussain, V. Dinesh Reddy, Ashu Abdul, Firoj Gazi

“…These include the Genetic Algorithm (GA), Non-dominated Sorting Genetic Algorithm II (NSGA-II), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and Teaching-Learning-Based Optimization (TLBO). …”
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Research on Fire Detection of Cotton Picker Based on Improved Algorithm by Zhai Shi, Fangwei Wu, Changjie Han, Dongdong Song

“…Therefore, in this study, we designed an improved algorithm for multi-sensor data fusion; built a cotton picker fire detection system by using infrared temperature sensors, CO sensors, and the upper computer; and proposed a BP neural network model based on improved mutation operator hybrid gray wolf optimizer and particle swarm optimization (MGWO-PSO) algorithm based on the BP neural network model. …”
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Comprehensive Research on Energy Saving Synergy Optimization and Optimal Real-time Control of Hybrid Electric Mining Trucks by Li Hongliang, Zhang Guojing, Fan Ping

“…This study takes the hybrid electric mining truck as a research object, establishes the mathematical model of the whole vehicle, takes reducing fuel consumption as the goal, establishes a collaborative optimization model that comprehensively considers the interaction between transmission system parameters and energy management strategies, and combines particle swarm optimization (PSO) algorithm and dynamic programming (DP) algorithm to build a two-layer interactive optimization algorithm to eliminate the interaction between transmission system parameters and energy management strategies. …”
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