An Improved Whale Optimization Algorithm for the Clean Production Transformation of Automotive Body Painting by Qin Yang, Xinning Li, Teng Yang, Hu Wu, Liwen Zhang

“…To reduce pollutants generated by automotive painting processes and improve coating efficiency, this study proposes a clean production method for automotive body painting based on an improved whale optimization algorithm from the perspective of “low-carbon consumption and emission-reduced production”. …”
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A Novel Improved Binary Optimization Algorithm and Its Application in FS Problems by Boyuan Wu, Jia Luo

“…Secondly, a multi-population evolutionary strategy is introduced, which takes into account the diversity of individuals based on fitness values to optimize the balance between exploration and exploitation stages of the algorithm, ultimately improving the algorithm’s capability to explore the FS solution space globally. …”
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Hybridization of deep learning models with crested porcupine optimizer algorithm-based cybersecurity detection on industrial IoT for smart city environments by Sarah A. Alzakari, Mohammed Aljebreen, Mashael M. Asiri, Wahida MANSOURI, Sultan Alahmari, Mohammed Alqahtani, Shaymaa Sorour, Wafi Bedewi

“…This study presents Cybersecurity using a Crested Porcupine Optimizer Algorithm with Hybrid Deep Learning Models (CCPOA-HDLM). …”
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An Improved Chaos Genetic Algorithm for T-Shaped MIMO Radar Antenna Array Optimization by Xin Fu, Xianzhong Chen, Qingwen Hou, Zhengpeng Wang, Yixin Yin

“…Improved chaotic genetic algorithm optimization model is established. …”
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Research on hybrid intrusion detection based on improved Harris Hawk optimization algorithm by Pengzhen Zhou, Huifu Zhang, Wei Liang

“…The improved Harris Hawk optimization algorithm is used as a feature selection scheme to reduce the impact of redundant and noisy features on the performance of the classification model. …”
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An Improved Adaptive Simulated Annealing Particle Swarm Optimization Algorithm for ARAIM Availability by Ershen Wang, Xiaozhu Shi, Xidan Deng, Jing Gao, Wei Zhang, Huan Wang, Song Xu

“…Aiming at this problem, we proposed an adaptive simulated annealing particle swarm optimization (ASAPSO) algorithm to redistribute integrity and continuity risks and establish a protection level optimization model. …”
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AOAFS: A Malware Detection System Using an Improved Arithmetic Optimization Algorithm by Rafat Alshorman, Bilal H. Abed-alguni, Yaqeen E. Alqudah

“…Finally, Dynamic Opposition-based Learning is utilized to improve the mutation capability of the AOAFS. Several malware datasets were used to compare the AOAFS to four popular Machine Learning algorithms and eight famous wrapper-based optimization algorithms. …”
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Application of Improved Whale Algorithm to Optimize Dephosphorization Process Parameters in Converter Steelmaking by Congrui Wu, Yueping Kong

“…This study addresses process parameter optimization challenges in converter steelmaking by proposing an improved multi-objective whale optimization algorithm (IMOWOA) that synergistically integrates metallurgical thermodynamics with data-driven modeling. …”
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Optimization of Offshore Wind and Wave Energy Co-Generation System Based on Improved Seagull Optimization Algorithm by Xiaoshi Zhuang, Honglue Wan, Dongran Song, Xinyu Fan, Yuchen Wang, Qian Huang, Jian Yang

“…Finally, a case study in the South China Sea validates the effectiveness of the model and algorithm. Using the improved algorithm, the optimal layout of the co-generation system and the optimal wind turbine parameters are obtained. …”
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Multi-objective Path Planning for AUVs Based on Improved Whale Optimization Algorithms and Fluid Disturbance Algorithms by Yuhong MA, Wen PANG, Daqi ZHU

“…To address the challenges of low path planning efficiency for autonomous undersea vehicle(AUV) in multi-target environments, as well as the limitations of the traditional whale optimization algorithm(WOA) in terms of susceptibility to local optima and inadequate adaptability to three-dimensional obstacle avoidance requirements, this study proposed a collaborative planning strategy that integrated a fluid perturbation algorithm with an improved WOA. …”
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Uncertainty prediction of wind speed based on improved multi-strategy hybrid models by Xinyi Xu, Shaojuan Ma, Cheng Huang

“…Due to insufficient traditional wind speed interval prediction methods for mining nonlinear features, in this paper, a novel interval prediction method was proposed by combining improved wavelet threshold and deep learning (BiTCN-BiGRU) with the nutcracker optimization algorithm (NOA). …”
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Optimization of Body Size and Centroid Position of the Quadruped Robot based on Improved Particle Swarm Optimization Algorithm by Kai Tang, Huanlong Wu, Liang′an Zhang, Ranming Ji, Yongjie Zhao, Xiaoyi Wang, Xinjian Lu

“…Taking the quadruped robot as research object， a method to optimize body size and centroid position of the quadruped robot based on improved particle swarm optimization algorithm to enhance its stability is proposed. …”
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TCN-LSTM-MHSA model optimized by improved slime mould algorithm for stress prediction of roadway anchor bolts (cables) by QI Junyan, CHE Yuhao, WANG Lei, YUAN Ruifu

“…To address this problem, an anchor bolt (cable) stress prediction model based on an Improved Slime Mould Algorithm (ISMA) optimized Temporal Convolutional Network (TCN)-Long Short-Term Memory (LSTM)-Multi-Head Self-Attention (MHSA) architecture is proposed. …”
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Heuristic Optimization-Assisted Dilated Convolution Neural Network With Gated Recurrent Unit for Channel Estimation in NOMA-OFDM System by Vijayakumar Kondepogu, Budhaditya Bhattacharyya

“…The loss functions in the model are optimized by using the Improved Pelican Optimization Algorithm (IPOA). …”
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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

“…The Beluga Whale Optimization (BWO) algorithm is a swarm intelligence optimization algorithm that can be used to optimize hyperparameters of deep learning models. …”
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An Improved Unscented Kalman Filter Applied to Positioning and Navigation of Autonomous Underwater Vehicles by Jinchao Zhao, Ya Zhang, Shizhong Li, Jiaxuan Wang, Lingling Fang, Luoyin Ning, Jinghao Feng, Jianwu Zhang

“…Excessive noise interference may cause a decrease in filtering accuracy and is highly likely to result in divergence by means of the traditional Unscented Kalman Filter, resulting in an increase in uncertainty factors during submersible mission execution. An estimation model for system noise, the adaptive Unscented Kalman Filter (UKF) algorithm was derived in light of the maximum likelihood criterion and optimized by applying the rolling-horizon estimation method, using the Newton–Raphson algorithm for the maximum likelihood estimation of noise statistics, and it was verified by simulation experiments using the Lie group inertial navigation error model. …”
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Advances in the Application of Intelligent Algorithms to the Optimization and Control of Hydrodynamic Noise: Improve Energy Efficiency and System Optimization by Maosen Xu, Bokai Fan, Renyong Lin, Rong Lin, Xian Wu, Shuihua Zheng, Yunqing Gu, Jiegang Mou

“…In recent years, intelligent algorithms represented by data-driven algorithms and heuristic algorithms have gradually emerged, showing great potential for development in hydrodynamic noise optimization applications. …”
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Research on Thickness Error Optimization Method of Rolling System Based on Improved Sparrow Search Algorithm–Bidirectional Long Short-Term Memory Network–Attention by Qingyun Wu, Xinchen Li, Jiafei Ji, Bowen Xing

“…Secondly, an improved sparrow search algorithm is used to search for the hyperparameters of the network to obtain better training results. …”
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Improving Parameter Estimation of Fuel Cell Using Honey Badger Optimization Algorithm by Rolla Almodfer, Mohammed Mudhsh, Samah Alshathri, Laith Abualigah, Laith Abualigah, Mohamed Abd Elaziz, Mohamed Abd Elaziz, Mohamed Abd Elaziz, Khurram Shahzad, Mohamed Issa

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Fault Diagnosis of Power Equipment Based on Improved SVM Algorithm by Youle Song, Yuting Duan, Tong Rao

“…Therefore, this study proposes an improved support vector machine model, combined with grey wolf optimization algorithm, aimed at improving the accuracy and efficiency of power equipment fault diagnosis. …”
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