Evolving the Whale Optimization Algorithm: The Development and Analysis of MISWOA by Chunfang Li, Yuqi Yao, Mingyi Jiang, Xinming Zhang, Linsen Song, Yiwen Zhang, Baoyan Zhao, Jingru Liu, Zhenglei Yu, Xinyang Du, Shouxin Ruan

“…This paper introduces an enhanced Whale Optimization Algorithm, named the Multi-Swarm Improved Spiral Whale Optimization Algorithm (MISWOA), designed to address the shortcomings of the traditional Whale Optimization Algorithm (WOA) in terms of global search capability and convergence velocity. …”
Get full text

An Advanced Whale Optimization Algorithm for Grayscale Image Enhancement by Yibo Han, Pei Hu, Zihan Su, Lu Liu, John Panneerselvam

“…New equations are incorporated into WOA to improve its global optimization capability, and exemplars and advanced spiral updates improve the convergence of the algorithm. …”
Get full text

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). …”
Get full text

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). …”
Get full text

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.…”
Get full text

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

Get full text

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). …”
Get full text

Modified Whale Optimization Algorithm for Multiclass Skin Cancer Classification by Abdul Majid, Masad A. Alrasheedi, Abdulmajeed Atiah Alharbi, Jeza Allohibi, Seung-Won Lee

“…To address these challenges, this paper proposes an innovative deep learning-based framework that integrates an ensemble of two pre-trained convolutional neural networks (CNNs), SqueezeNet and InceptionResNet-V2, combined with an improved Whale Optimization Algorithm (WOA) for feature selection. …”
Get full text

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. …”
Get full text

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

Subjects: Get full text

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.…”
Get full text

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. …”
Get full text

Microservice combination optimisation based on improved gray wolf algorithm by Jingjing Hu, Xiaojun Xu, Jin Hao, Xiuqi Yang, Kefan Qiu, Yuanzhang Li

Get full text

Hybrid Deep Learning Techniques for Improved Anomaly Detection in IoT Environments by Hanan Abbas Mohammad

Get full text

An Improved Coral Reef Optimization-Based Scheduling Algorithm for Cloud Computing by Shuzhen Wan, Lixin Qi

“…In this paper, we establish a resource allocation framework and propose a novel task scheduling algorithm. An improved coral reef optimization (ICRO) is proposed to deal with this task scheduling problem. …”
Get full text

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). …”
Get full text

A multistrategy improved hunger games search algorithm by Qiu Yihui, Zhang Xinqiang, Li Ruoyu, Li Dongyi, Xia Feihan

“…Abstract In this paper, we propose a multistrategy improved Hunger Games Search (MHGS) algorithm to address several inherent limitations of the original HGS, including imbalanced exploration and exploitation, insufficient population diversity, and premature convergence. …”
Get full text

Comparative study of whale optimization algorithm and flower pollination algorithm to solve workers assignment problem by Huthaifa Al-Khazraji

“…Two metaheuristic optimizations named Whale Optimization Algorithm (WOA) and Flower Pollination Algorithm (FPA) are utilized to final the optimal solution that reduces the total cost. …”
Get full text

A Multi-Strategy Improved Horned Lizard Optimization Algorithm and Its Application in Engineering Optimization by Yancang Li, Jinfan Zhang, Zidong Jin, Weitao Qiao

“…In this study, a multi-strategy improved horned lizard optimization algorithm (MSHLOA) is proposed to overcome the limitations of the standard HLOA in terms of premature convergence and slow optimization search. …”
Get full text

LSEWOA: An Enhanced Whale Optimization Algorithm with Multi-Strategy for Numerical and Engineering Design Optimization Problems by Junhao Wei, Yanzhao Gu, Yuzheng Yan, Zikun Li, Baili Lu, Shirou Pan, Ngai Cheong

“…The Whale Optimization Algorithm (WOA) is a bio-inspired metaheuristic algorithm known for its simple structure and ease of implementation. …”
Get full text