An efficient enhanced exponential distribution optimizer: applications in global, engineering, and combinatorial optimization problems by Marwa M. Emam, Mohammed R. Saad, Mina Younan, Essam H. Houssein

“…The optimizers include the improved multi-operator differential evolution algorithm (IMODE), adaptive guided differential evolution algorithm (AGDE), whale optimization algorithm (WOA), grey wolf optimizer (GWO), sinh cosh optimizer (SCHO), RIME optimization algorithm (RIME), and the original EDO. …”
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MULTI-OBJECTIVE OPTIMIZATION DESIGN FOR CUTTING MECHANISM OF ROADHEADER BASED ON IMPROVED GENETIC ALGORITHM by MAO Jun, PAN DeWen, XIE Miao, ZHENG GuangHui

“…This paper takes motion parameters and structure parameters of cutting mechanism for design variables and optimizes multi-objective function of comprehensive performance of cutting mechanism based on the improved genetic algorithm. …”
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Pressure sensor placement in water distribution networks based on enhanced Rafflesia optimization algorithm by Yu‐Chung Huang, Qingyong Yang, Shu‐Chuan Chu, Jeng‐Shyang Pan

“…This letter proposes an enhanced Rafflesia optimization algorithm (EROA) to solve this problem. …”
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Neutrosophic Simulated Annealing Algorithm and Its Application in Operation Optimization in Dangerous Goods Warehouse by Fangwei Zhang, Zhenrui Chen, Jun Ye, Bing Han

“…The biggest contribution of this study is to propose a novel entropy measurement method using the NFS and combine it with the simulated annealing algorithm to handle the optimization process. Finally, the effectiveness of the novel algorithm is verified by an example of warehouse optimization.…”
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A novel elite guidance-based social learning particle swarm optimization algorithm by QI Cheng, XIE Junwei, WANG Xue, FENG Weike, ZHANG Haowei

“…To improve the premature convergence and poor global search capability of the classical particle swarm algorithm(PSO), this paper proposes a novel elite guidance-based social learning particle swarm optimization (ESLPSO) algorithm. …”
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IWOA-LSTM based intrinsic structural identification of steel fiber concrete by Ping Li, Jie Feng, Shiwei Duan

“…Firstly, the Laplace crossover operator strategy, the optimal neighbourhood perturbation strategy, the adaptive weighting strategy and the updating strategy of the variables helix position are introduced to solve the problems of the Whale Optimisation Algorithm (WOA) in relation to its slow convergence rate and its tendency to fall into the locally optimal solution. …”
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Research on intelligent control of coal slime flotation based on the WOA-GRU model by DOU Zhiheng, WANG Ranfeng, QIN Xinkai, CHAI Yuqing, LI Pinyu, LIU Shutong

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Harnessing synergy of machine learning and nature-inspired optimization for enhanced compressive strength prediction in concrete by Abba Bashir, Esar Ahmad, Shashivendra Dulawat, Sani I. Abba

“…This study assesses nine machine learning models, integrating conventional AI algorithms, such as artificial neural network (ANN), support vector regression (SVR), and random forest (RF) with nature-inspired optimization techniques including chicken swarm optimization (CSO), moth flame optimization algorithm (MFO), and whale optimization algorithm (WOA). …”
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A multi task learning framework using DeBERTa and BWO optimization for enhancing long term english vocabulary memory by Jiasheng Zhu

“…This paper uses DeBERTa (Decoding-enhanced BERT with disentangled attention) to perform word part-of-speech classification and meaning matching, and uses BWO (Beluga Whale Optimization) to optimize hyperparameters and loss weights to alleviate the problem of memory decay and improve the depth and complexity of English word memory. …”
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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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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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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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Energy efficient optimal sink position selection algorithm for multi-sink wireless sensor networks by TANG Wei, GUO Wei

“…In combination with the energy efficient routing algorithm,the optimal sink position selection problem was studied,which aimed to minimize the overall network energy consumption.When the candidate set of sink positions is finite,the problem is shown to be an integer linear programming problem,when the candidate set is the whole space,the problem is shown to be a nonlinear programming problem.Due to the NP-completeness of the problems,several heuristic algorithms were designed accordingly.The proposed algorithms were examined by extensive simulation experiments,the results show that the performances of presented algorithms are close to the optimality.…”
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Research on a stable clustering algorithm based on the optimal connectivity power for wireless sensor networks by LI Fang-min1, LIU Xin-hua1, KUANG Hai-lan1, FANG Yi-lin1

“…In realistic environment, the actual layout of nodes is easy to make network separated and nodes are always densely deployed in hot spots like the site of an accident or disaster where the competition intense was very high.A stable clustering algorithm based on the optimal connectivity power for wireless sensor networks was proposed.The algorithm makes use of the alterable power control technology to raise the channel utilization ratio and network throughput based on the optimal number of neighbors, and realizes the stable connectivity and clustering of network.The algorithm simplifies the topology of network so that prolong the network lifetime at the best.The simulation results show that the algorithm maintains the connectivity and stability of network effectively, and has good auto-adapted ability to environment and obvious effects in the promotion of whole performance of network.…”
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An Optimized Dynamic Scene Change Detection Algorithm for H.264/AVC Encoded Video Sequences by Giorgio Rascioni, Susanna Spinsante, Ennio Gambi

“…This paper deals with the design and performance evaluation of a dynamic scene change detector optimized for H.264/AVC encoded video sequences. The detector is based on a dynamic threshold that adaptively tracks different features of the video sequence, to increase the whole scheme accuracy in correctly locating true scene changes. …”
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Simulation of Natural Gas Pipeline Networks Based on Roughness Optimization Algorithm and Global Mesh Refinement by Yi Yang

“…ABSTRACT Natural gas pipeline network simulation technology is the fundamental technology of system capacity analysis, pipeline design, operation planning and optimization as well as emergency decision‐making for the whole life cycle of a given pipeline network system. …”
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Heat transfer and simulated coronary circulation system optimization algorithms for real power loss reduction by Kanagasabai L.

“…In this paper, the heat transfer optimization (HTO) algorithm and simulated coronary circulation system (SCCS) optimization algorithm has been designed for Real power loss reduction. …”
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A multi-objective optimization-based ensemble neural network wind speed prediction model by Haoyuan Ma, Chang Liu, Ziyuan Qiao, Yuan Liang, Hongqing Wang

“…Built upon the NSGA-II framework, NS-ADPOA enhances offspring generation by leveraging a probabilistic error-driven fusion of Particle Swarm Optimization (PSO) and Whale Optimization Algorithm (WOA), combining their strengths in local and global search, respectively. …”
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