Optimizing Solid Rocket Missile Trajectories: A Hybrid Approach Using an Evolutionary Algorithm and Machine Learning by Carlo Ferro, Matteo Cafaro, Paolo Maggiore

“…This paper introduces a novel approach for modeling and optimizing the trajectory and behavior of small solid rocket missiles. …”
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Optimization of energy consumption in mobile Ad-Hoc networks with a swarm intelligence-based ABC algorithm by Vijay U. Rathod, Shyamrao V. Gumaste, Ramakrishna Guttula, Shrikant Zade, Ramanpreet Singh

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Research on multi-objective optimization method for bullet full trajectory based on SA-PSO hybrid algorithm by HU Zhenchao, CUI Xiao, XU Xiao, LU Dabin, ZHANG Huisheng

“…The results demonstrate that this approach converges to the optimal solution more efficiently compared to traditional algorithms. …”
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An optimized feature selection using triangle mutation rule and restart strategy in enhanced slime mould algorithm by Ibrahim Musa Conteh, Gibril Njai, Abass Conteh, Qingguo Du

“…This paper proposes an improved feature selection method based on an improved Slime Mould Algorithm (SMA), called the Triangular Mutation Rule Restart Strategy Slime Mould Algorithm (TRSMA), to overcome some of the shortcomings of the SMA, including premature convergence, poor population diversity, and local optima entrapment. …”
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Optimal Reactive Power Generation for Radial Distribution Systems Using a Highly Effective Proposed Algorithm by Le Chi Kien, Thuan Thanh Nguyen, Bach Hoang Dinh, Thang Trung Nguyen

“…In this paper, a proposed modified stochastic fractal search algorithm (MSFS) is applied to find the most appropriate site and size of capacitor banks for distribution systems with 33, 69, and 85 buses. …”
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Enhanced vehicle routing for medical waste management via hybrid deep reinforcement learning and optimization algorithms by Norhan Khallaf, Osama Abd-El Rouf, Abeer D. Algarni, Mohy Hadhoud, Ahmed Kafafy

“…This approach not only improved performance but also enhanced environmental sustainability, making it the most effective and challenging solution among all the algorithms used in the study.…”
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The Study of Roadside Visual Perception in Internet of Vehicles Based on Improved YOLOv5 and CombineSORT by LI Xiaohui, YANG Jie, XIA Qin

“…It indicates that most algorithms can achieve good detection results when the targets are sparse, and the lightweight models may have more advantages with considering the demand of computing resources. …”
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A comparative study of the performance of ten metaheuristic algorithms for parameter estimation of solar photovoltaic models by Adel Zga, Farouq Zitouni, Saad Harous, Karam Sallam, Abdulaziz S. Almazyad, Guojiang Xiong, Ali Wagdy Mohamed

“…The Friedman test was utilized to rank the performance of the various algorithms, revealing the Growth Optimizer as the top performer across all the considered models. …”
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Applications of Metaheuristic Algorithms in Solar Air Heater Optimization: A Review of Recent Trends and Future Prospects by Jean De Dieu Niyonteze, Fumin Zou, Godwin Norense Osarumwense Asemota, Walter Nsengiyumva, Noel Hagumimana, Longyun Huang, Aphrodis Nduwamungu, Samuel Bimenyimana

“…Therefore, this paper clearly shows that the use of all six proposed metaheuristic algorithms results in significant efficiency improvements through the selection of the optimal design set and operating parameters for SAHs. …”
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PCA-FSA-MLR Model and Its Application in Runoff Forecast by GUO Cunwen, CUI Dongwen

“…To improve the accuracy of runoff forecast,and establish a runoff forecast model combining principal component analysis (PCA),future search algorithm (FSA),and multiple linear regression (MLR),this paper reduces the dimensionality of the sample data by PCA,selects 8 standard test functions and simulates and verifies FSA under different dimensional conditions,optimizes MLR constant terms and partial regression coefficients by FSA,proposes a PCA-FSA-MLR runoff forecast model,constructs PCA-LS-MLR,PCA-FSA-SVM,and PCA-SVM models with dimensionality reduction processing by PCA and FSA-MLR,LS-MLR,FSA-SVM,and SVM without dimensionality reduction processing as a comparison model,and verifies each model through forecasting the annual runoff and monthly runoff in December of Longtan station in Yunnan Province.The results show that:①FSA has better optimization accuracy and global extremum search ability under different dimensional conditions;②The average absolute relative error of the annual runoff and monthly runoff in December of Longtan station through PCA-FSA-MLR model are 1.63% and 3.91% respectively,and its forecast accuracy is better than the other 7 models,with higher forecast accuracy and stronger generalization ability;③For the same model,the forecast accuracy after dimensionality reduction processing by PCA is better than that without dimensionality reduction processing,so the data dimensionality reduction by PCA is helpful to improve the forecast accuracy of models.…”
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Enhancing image retrieval through optimal barcode representation by Rasa Khosrowshahli, Farnaz Kheiri, Azam Asilian Bidgoli, H. R. Tizhoosh, Masoud Makrehchi, Shahryar Rahnamayan

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The Optimal Cost Design of Reinforced Concrete Beams Using an Artificial Neural Network—The Effectiveness of Cost-Optimized Training Data by Jaemin So, Seungjae Lee, Jonghyeok Seong, Donwoo Lee

“…This study presents a method for the automated design of reinforced concrete (RC) beam cross-sections using an artificial neural network (ANN) trained with cost-optimized data generated by the crow search algorithm (CSA). …”
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An optimized informer model design for electric vehicle SOC prediction. by Xin Xie, Feng Huang, Yefeng Long, Youyuan Peng, Wenjuan Zhou

“…Therefore, based on the health assessment algorithm, a new optimized Informer model is proposed to predict SOC. …”
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Machine learning-based coalbed methane well production prediction and fracturing parameter optimization by HU Qiujia, LIU Chunchun, ZHANG Jianguo, CUI Xinrui, WANG Qian, WANG Qi, LI Jun, HE Shan

“…The model employs a random forest algorithm integrated with a multi-task learning strategy and utilizes a particle swarm optimization (PSO) algorithm to optimize fracturing parameters. …”
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An Intelligent 5G Unmanned Aerial Vehicle Path Optimization Algorithm for Offshore Wind Farm Inspection by Congxiao Jiang, Lingang Yang, Yuqing Gao, Jie Zhao, Wenne Hou, Fangmin Xu

“…We propose a novel Sea Wind-Aware Improved A*-Guided Genetic Algorithm (SWA-IAGA), which integrates an improved A* algorithm to guide the genetic algorithm for efficient path planning, with the assistance of relevant graphical knowledge. …”
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Volute Optimization Based on Self-Adaption Kriging Surrogate Model by Fannian Meng, Ziqi Zhang, Liangwen Wang

“…Optimizing the volute performance can effectively improve the efficiency of a centrifugal fan by changing the volute geometric parameter, so the self-adaption Kriging surrogate model is used to optimize the volute geometric parameter. …”
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Charging path optimization in mobile wireless rechargeable sensor networks by Quanlong NIU, Riheng JIA, Minglu LI

“…The wireless power transfer technique is promising in solving the energy bottleneck of sensor nodes in wireless sensor networks, which can thus prolong the network lifetime or even maintain sustainable network operations.Most existing works focused on optimizing the static chargers’ deployment or mobile chargers’ charging path for static sensor nodes with fixed sensor node positions, ignoring the scenario with mobile sensor nodes.Thus, design and optimize the charging path of a mobile charger was studied for dynamic wireless sensor networks with mobile sensor nodes, to maximize the charging utility within a finite time horizon, that is, the charger can encounter as more sensor nodes as possible in a limited time and charge them.Notice that the mobile charger may stop to simultaneously charge multiple nodes within its charging range during its charging tour.The proposed charging path optimization problem was proven to be an APX-hard problem.Then, based on the constructed directed acyclic graph using discretization method, a layer-wise pruning algorithm based on the backtracking method was proposed.The proposed algorithm took the solution generated by the greedy algorithm as the benchmark and searched the optimal charging path under a fixed time division by layer-wise pruning.Simulation results show that the proposed algorithm can effectively improve the charging utility .…”
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Charging path optimization in mobile wireless rechargeable sensor networks by Quanlong NIU, Riheng JIA, Minglu LI

“…The wireless power transfer technique is promising in solving the energy bottleneck of sensor nodes in wireless sensor networks, which can thus prolong the network lifetime or even maintain sustainable network operations.Most existing works focused on optimizing the static chargers’ deployment or mobile chargers’ charging path for static sensor nodes with fixed sensor node positions, ignoring the scenario with mobile sensor nodes.Thus, design and optimize the charging path of a mobile charger was studied for dynamic wireless sensor networks with mobile sensor nodes, to maximize the charging utility within a finite time horizon, that is, the charger can encounter as more sensor nodes as possible in a limited time and charge them.Notice that the mobile charger may stop to simultaneously charge multiple nodes within its charging range during its charging tour.The proposed charging path optimization problem was proven to be an APX-hard problem.Then, based on the constructed directed acyclic graph using discretization method, a layer-wise pruning algorithm based on the backtracking method was proposed.The proposed algorithm took the solution generated by the greedy algorithm as the benchmark and searched the optimal charging path under a fixed time division by layer-wise pruning.Simulation results show that the proposed algorithm can effectively improve the charging utility .…”
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Locality-guided based optimization method for bounded model checker by Shun WANG, Ye DU, Zhen HAN, Jiqiang LIU

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Optimizing Virtual Power Plant Performance through Three-Phase Power Flow Analysis and TCAS Algorithm by Meisam Azimi, Mehdi Foroughi, Mohammad Hadi Foroughi, Moein Moeini-Aghtaie, Hossein Yousefi, Mohammad Behzad Hadi

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