A novel hybrid methodology for wind speed and solar irradiance forecasting based on improved whale optimized regularized extreme learning machine by S. Syama, J. Ramprabhakar, R Anand, V. P. Meena, Josep M. Guerrero

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Parameter Tuning of A Binary Pareto Whale Optimization Algorithm Using Taguchi Grey Relational Analysis by Haleel Aseel Jameel, Dawood Lamyaa Mohammed

“…The aim of this paper is to investigate the optimal control parameter values for the Binary Pareto Whale Optimization Algorithm BPWOA, which is used for solving maintenance scheduling problem at a power plant. …”
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Interline Power Flow Controller Allocation for Active Power Losses Enhancement Using Whale Optimization Algorithm by Ahmed M. Alshannaq, Mohammed A. Haj-ahmed, Mais Aldwaik, Dia Abualnadi

“…In this paper, the interline power flow controller’s impact on transmission network performance is investigated as it is implemented within the IEEE 5-bus, 14-bus, and IEEE 57-bus systems. In addition, the whale optimization algorithm (WOA) is used to optimize the interline power flow controller locations within the system to achieve optimal transmission system performance. …”
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Two-layer optimization model of distribution network line loss considering the uncertainty of new energy access by Xiping Ma, Xiping Ma, Xiaoyang Dong, Haitao Xiao, Yaxin Li, Rui Xu, Kai Wei, Juanjuan Cai, Juan Wei

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Improvement analysis of organic light emitting diode temperature control by integrating whale algorithm in PID control system. by Dayu Zhang, Cong Guan

“…To solve this problem, the study proposes an improved PID controller based on the Long Short-Term Memory (LSTM) optimized by the Whale Optimization Algorithm (WOA). …”
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Charging pile fault prediction method combining whale optimization algorithm and long short-term memory network by Yansheng Huang, Atthapol Ngaopitakkul, Suntiti Yoomak

“…By introducing the whale optimization mechanism to globally optimize the key parameters of the neural network, the method improved the model’s ability to model complex time series data. …”
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Study on High Efficiency Control of Four-Switch Buck-Boost Converter Based on Whale Migration Optimization Algorithm by Zhencheng Hao, Yu Xu, Jing Bai

“…In this paper, an optimization algorithm is combined with the multi-mode control of an FSBB converter for the first time, and a combined optimization and voltage closed-loop control strategy based on the Whale Migration Algorithm (WMA) is proposed. …”
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ML-based approach to potato diseases diagnosis using image processing and whale optimization algorithm for feature selection by Zhongxu Li, Seyed Mohamad Javidan

“…Nature-inspired feature extraction techniques, such as the Whale Optimization Algorithm (WOA), have gained considerable attention recently. …”
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Comprehensive Study of Nonlinear Maglev System Utilizing COOT Optimized FOPID Controller by Marabathina Maheedhar, T. Deepa

“…The contribution of the proposed work is two different algorithms, including the Genetic Algorithm and Whale Optimization Algorithm, were used to contrast the effectiveness of the FOPID controller based on the COOT method. …”
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(IoT) Network intrusion detection system using optimization algorithms by Luo Shan

“…Abstract To address the complex requirements of network intrusion detection in IoT environments, this study proposes a hybrid intelligent framework that integrates the Whale Optimization Algorithm (WOA) and the Grey Wolf Optimization (GWO) algorithm—referred to as WOA-GWO. …”
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Low Carbon Economic Dispatch of Power System Based on Multi-Region Distributed Multi-Gradient Whale Optimization Algorithm by Linfei Yin, Yongzi Ye, Xiaoping Xiong, Jiajia Chai, Hanzhong Cui, Haoyuan Li

“…This study establishes a multi-region distributed optimization model and combines the multi-region distributed optimization model with a multi-gradient optimization algorithm to propose a multi-region distributed multi-gradient whale optimization algorithm (MRDMGWOA). …”
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Application of improved particle swarm optimization algorithm combined with genetic algorithm in shear wall design by Wei Gao

“…The improved algorithm is based on the basic framework of genetic algorithm and particle swarm optimization algorithm, first adjusting the inertia weight, and then introducing elimination mechanism and mutation rate control. …”
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FDIA Detection in Power Grid Based on Opposition-Based Whale Optimization Algorithm and Multi-layer Extreme Learning Machine by Lei XI, Yixiao WANG, Miao HE, Chen CHENG, Xilong TIAN

“…The proposed method not only extends the extreme learning machine into a multi-layer neural network to solve the problem of its limited ability of feature expression, but also introduces the whale optimization algorithm to optimize the number of neurons of the multi-layer extreme learning machine, and uses the opposition-based learning strategy to improve its convergence speed and detection accuracy so as to prevent the influence of randomly determining the number of neurons in each hidden layer on the generalization performance and location detection results of the detection method. …”
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Aging Prediction of IGBT Based on Improved Support Vector Regression by Zhengxiong CHEN, Mahemuti PAZILAI, Wei SHEN

“…In order to accurately predict the aging state of insulated gate bipolar transistor (IGBT), a novel IGBT aging prediction method is proposed based on improved whale optimization algorithm (IWOA) and optimized support vector regression (SVR). …”
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Improved PESA algorithm based on comentropy by Kun WANG, Lin-lin WANG, Yan LIU, Yu-hua ZHANG, Meng WU

“…Simula-tion results show that the computational effort of C-PESA increases linearly with the rising number of solutions. Mean-while, the computation time is improved almost four times, and the evolutionary computation efficiency is also enhanced.…”
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Optimizing Deep Learning Models with Improved BWO for TEC Prediction by Yi Chen, Haijun Liu, Weifeng Shan, Yuan Yao, Lili Xing, Haoran Wang, Kunpeng Zhang

“…This paper analyzed the drawbacks of BWO and proposed an improved BWO algorithm, named FAMBWO (Firefly Assisted Multi-strategy Beluga Whale Optimization). …”
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Improved sine cosine algorithm for large-scale optimization problems by ZHANG Chao, YANG Yi

“…Compared with the improved wolf pack algorithm (IWPA), the improved flower pollination algorithm (IFPA), the improved whale optimization algorithm (IWOA), and the modified whale optimization algorithm (MWOA), which are suitable for solving large scale optimization problems, it is found that the overall optimization result of SCAL is better than the comparison algorithms and thus demonstrate that the proposed algorithm has the obvious advantages and competitiveness for solving large-scale optimization problems.…”
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An improved beluga whale optimizer-Derived Adaptive multi-channel DeepLabv3+ for semantic segmentation of aerial images. by Anilkumar P, Venugopal P

“…This model has adopted a new Adaptive Multichannel Deeplabv3+ (AMC-Deeplabv3+) with the help of a new meta-heuristic algorithm called Improved Beluga whale optimization (IBWO). …”
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Improved grey wolf optimization algorithm based service function chain mapping algorithm by Yue ZHANG, Junnan ZHANG, Xiaochun WU, Chen HONG, Jingjing ZHOU

“…With the rise of new Internet applications such as the industrial Internet, the Internet of vehicles, and the metaverse, the network’s requirements for low latency, reliability, security, and certainty are facing severe challenges.In the process of virtual network deployment, when using network function virtualization technology, there were problems such as low service function chain mapping efficiency and high deployment resource overhead.The node activation cost and instantiation cost was jointly considered, an integer linear programming model with the optimization goal of minimizing the average deployment network cost was established, and an improved grey wolf optimization service function chain mapping (IMGWO-SFCM) algorithm was proposed.Three strategies: mapping scheme search based on acyclic KSP algorithm, mapping scheme coding and improvement based on reverse learning and nonlinear convergence were added to the standard grey wolf optimization algorithm to form this algorithm.The global search and local search capabilities were well balanced and the service function chain mapping scheme was quickly determined by IMGWO-SFCM.Compared with the comparison algorithm, IMGWO-SFCM reduces the average deployment network cost by 11.86% while ensuring a higher service function chain request acceptance rate.…”
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Chain hybrid feature selection algorithm based on improved Grey Wolf Optimization algorithm. by Xiaotong Bai, Yuefeng Zheng, Yang Lu, Yongtao Shi

“…In particular, the wrapper algorithm is an improved Grey Wolf Optimization (IGWO) algorithm based on random disturbance factors, while the parameters are adjusted to vary randomly to make the population variations rich in diversity. …”
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