Dynamic Optimization of Xylitol Production Using Legendre-Based Control Parameterization by Eugenia Gutiérrez, Marianela Noriega, Cecilia Fernández, Nadia Pantano, Leandro Rodriguez, Gustavo Scaglia

“…The proposed technique employs Legendre polynomials to parameterize two control actions (the feeding rates of glucose and xylose), and it uses a hybrid optimization algorithm combining Monte Carlo sampling with genetic algorithms for coefficient selection. …”
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A multi task learning framework using DeBERTa and BWO optimization for enhancing long term english vocabulary memory by Jiasheng Zhu

“…Compared with PSO (Particle Swarm Optimization), GA (Genetic Algorithm) and GWO (Grey Wolf Optimizer), BWO showed better English word memory rate in cross-domain tests and under cognitive interference. …”
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ACOFuzz: An ant colony algorithm-based fuzzer for smart contracts by Peixuan Feng, Wenrui Cao, Siqi Lu, Yongjuan Wang, Haoyuan Xue, Runnan Yang

“…ACOFuzz employs the ant colony optimization (ACO) algorithm to traverse the control flow graph (CFG) of smart contracts, systematically exploring execution paths and generating test cases. …”
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COMQ: A Backpropagation-Free Algorithm for Post-Training Quantization by Aozhong Zhang, Zi Yang, Naigang Wang, Yingyong Qi, Jack Xin, Xin Li, Penghang Yin

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Optimal Coordination of Directional Overcurrent Relays Using an Innovative Fractional-Order Derivative War Algorithm by Bakht Muhammad Khan, Abdul Wadood, Herie Park, Shahbaz Khan, Husan Ali

“…This innovative approach integrates the principles of fractional calculus (FC) into the conventional war optimization (WO) algorithm, significantly improving its optimization properties. …”
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Prediction method of soil water content based on SVM optimized by improved salp swarm algorithm by Xiaoqiang ZHAO, Fan YANG, Zhufeng YAN

“…Aiming at the problems of low accuracy and low efficiency of traditional soil water content prediction methods, support vector machine (SVM) was used to establish a prediction model, and the soil water content prediction method based on SVM optimized was proposed by the improved salp swarm algorithm.Firstly, the opposition-based learning and chaotic optimization were introduced to improve the standard salp swarm algorithm to solve the problem that the algorithm was easy to fall into the local optimal solution and its convergence speed was slow.Secondly, the improved salp swarm algorithm was used to optimize the parameters that affect the performance of SVM and the corresponding prediction model was built.Finally, the proposed model was compared with the particle swarm optimization SVM and the whale algorithm optimized SVM prediction model.The experimental results show that the mean square error and decision coefficient of the proposed model are 0.42 and 0.901, which are better than the other two models which verified the effectiveness of the proposed method.…”
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Prediction method of soil water content based on SVM optimized by improved salp swarm algorithm by Xiaoqiang ZHAO, Fan YANG, Zhufeng YAN

“…Aiming at the problems of low accuracy and low efficiency of traditional soil water content prediction methods, support vector machine (SVM) was used to establish a prediction model, and the soil water content prediction method based on SVM optimized was proposed by the improved salp swarm algorithm.Firstly, the opposition-based learning and chaotic optimization were introduced to improve the standard salp swarm algorithm to solve the problem that the algorithm was easy to fall into the local optimal solution and its convergence speed was slow.Secondly, the improved salp swarm algorithm was used to optimize the parameters that affect the performance of SVM and the corresponding prediction model was built.Finally, the proposed model was compared with the particle swarm optimization SVM and the whale algorithm optimized SVM prediction model.The experimental results show that the mean square error and decision coefficient of the proposed model are 0.42 and 0.901, which are better than the other two models which verified the effectiveness of the proposed method.…”
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Intelligent Modeling and Experimental Investigation of the Collar's Impact on Reducing Scour around the Spur Dike by Hojat Karami, Alireza Rezaei, Amin Atarodi

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Lithium-ion battery RUL prediction based on optimized VMD-SSA-PatchTST algorithm by Pei Tang, Zetao Qiu, Zhongran Yao, Jiahao Pan, Dashuai Cheng, Xiaoyong Gu, Changcheng Sun

“…To enhance decomposition quality, the Whale Optimization Algorithm (WOA) optimizes the number of modes K and penalty factor α by minimizing mean envelope entropy. …”
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Solving MRTA problem based on multi-strategy genetic algorithm by CHEN Haiyang, LIU Yan, DOU Wei, HUANG Qi

“…Secondly, the population was divided into three parts to enhance the quality of chromosomes while maintaining randomness. Then, heuristic crossover operators were used to expand the search range of the solution and increase the algorithm′s ability to jump out of local optima. …”
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Multi-Objective Optimization for the Low-Carbon Operation of Integrated Energy Systems Based on an Improved Genetic Algorithm by Yao Duan, Chong Gao, Zhiheng Xu, Songyan Ren, Donghong Wu

“…This paper proposes an improved genetic algorithm (IGA) designed to optimize the multi-objective low-carbon operations of IESs, aiming to minimize both operating costs and carbon emissions. …”
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Electric vehicle battery state of charge estimation using metaheuristic-optimized CatBoost algorithms by Mohd Herwan Sulaiman, Zuriani Mustaffa, Ahmad Salihin Samsudin, Amir Izzani Mohamed, Mohd Mawardi Saari

“…Three distinct metaheuristic algorithms were investigated: Barnacles Mating Optimizer (BMO), Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Whale Optimization Algorithm (WOA), each integrated with CatBoost to optimize critical parameters including learning rate, tree depth, regularization, and bagging temperature. …”
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GWO and WOA variable step MPPT algorithms-based PV system output power optimization by Abderrahim Zemmit, Abdelouadoud Loukriz, Khaled Belhouchet, Yahya Z. Alharthi, Muhannad Alshareef, Prabhu Paramasivam, Sherif S. M. Ghoneim

“…This study proposes two innovative Maximum Power Point Tracking (MPPT) algorithms based on the Whale Optimization Algorithm (WOA) and Grey Wolf Optimization (GWO). …”
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Encryption Algorithm MLOL: Security and Efficiency Enhancement Based on the LOL Framework by Xinyue Zhang, Daoguang Mu, Wenzheng Zhang, Xinfeng Dong

“…In this paper, we present MLOL, a novel AEAD algorithm based on the LOL framework. MLOL combines authenticated encryption with optimizations to the LFSR structure to enhance both security and efficiency. …”
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Enhanced skill optimization algorithm: Solution to the stochastic reactive power dispatch framework with optimal inclusion of renewable resources using large‐scale network by Noor Habib Khan, Yong Wang, Raheela Jamal, Sheeraz Iqbal, Mohamed Ebeed, Yazeed Yasin Ghadi, Z. M. S. Elbarbary

“…The normal, lognormal, and Weibull distributions are utilized to model system uncertainties, while Monte‐Carlo simulation and reduction‐based approaches are utilized to generate the novel set of optimal scenarios. …”
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A Markov decision optimization of medical service resources for two-class patient queues in emergency departments via particle swarm optimization algorithm by Chia-Hung Wang, Rong Tian, Kun Hu, Yu-Tin Chen, Tien-Hsiung Ku

“…The particle swarm optimization algorithm was applied to determine the optimal number of servers, service rate, and number of beds. …”
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Multi-strategy enterprise development optimizer for numerical optimization and constrained problems by Xinyu Cai, Weibin Wang, Yijiang Wang

“…However, the analysis of the EDO algorithm shows that it suffers from the defects of rapidly decreasing population diversity and weak exploitation ability when dealing with complex optimization problems, while its algorithmic structure has room for further enhancement in the optimization process. …”
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Explainable Artificial Intelligence in Malignant Lymphoma Classification: Optimized DenseNet121 Deep Learning Approach With Particle Swarm Optimization and Genetic Algorithm by Haitham ELwahsh, Ali Bakhiet, Omar Ibrahim Alirr, Tarek Khalifa, Maazen Alsabaan, Mohamed I. Ibrahem, Engy El-Shafeiy

“…It is recommended that the combined application of PSO for feature reduction and GA for model optimization can be successfully used for improving accuracy rate of such algorithms while reducing computation time. …”
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Optimization of the Mechanical Property of Friction Stir Welded Heat Treatable Aluminum Alloy by using Bio-Inspired Artificial Intelligence Algorithms by Akshansh Mishra, Anish Dasgupta

“…The main objective of the work is to obtain the maximum optimized Ultimate Tensile Strength (MPa) by using Bio-Inspired Artificial Intelligence Algorithms i.e., Differential Evolution and Max Lipschitz optimization (Max LIPO) Algorithm. …”
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Optimization of the Mechanical Property of Friction Stir Welded Heat Treatable Aluminum Alloy by using Bio-Inspired Artificial Intelligence Algorithms by Akshansh Mishra, Anish Dasgupta

“…The main objective of the work is to obtain the maximum optimized Ultimate Tensile Strength (MPa) by using Bio-Inspired Artificial Intelligence Algorithms i.e., Differential Evolution and Max Lipschitz optimization (Max LIPO) Algorithm. …”
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