Digital Watermarking using Dragonfly Optimization Algorithm by Satender Sharma, Usha Chauhan, Ruqaiya Khanam, Krishna Kant Singh

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VNE-AFS:virtual network embedding based on artificial fish swarm by Qiang ZHU, Hui-qiang WANG, Hong-wu LV, Zhen-dong WANG

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Dholes Hunting—A Multi-Local Search Algorithm Using Gradient Approximation and Its Application for Blockchain Consensus Problem by Binh Minh Nguyen, Thieu Nguyen, Quoc-Hien Vu, Tran Huy Hung, Tran Hoang Hai, Huynh Thi Thanh Binh, Van-Dang Tran

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Multiobjective Time-Space Grid Optimization of Lithium-Ion Electrochemical Model Based on Stability Analysis and Limit Region Decoupling Strategy by Libin Zhang, Minghang Zhang, Hongying Shan, Guan Xu, Jingsheng Dong, Xuemeng Bai

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An improved pelican optimization algorithm for function optimization and constrained engineering design problems by Haval Tariq Sadeeq, Araz Abrahim, Thamer Hameed, Najdavan Kako, Reber Mohammed, Dindar Ahmed

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Sperm swarm optimization for many objective power flow problems with enhanced performance evaluation in power systems by Wulfran Fendzi Mbasso, Ambe Harrison, Pradeep Jangir, Idriss Dagal, Hossam Kotb, Njimboh Henry Alombah, Raman Kumar, Aseel Smerat, Emmanuel Fendzi Donfack, Saad F. Al-Gahtani, Z. M. S. Elbarbary

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Driver identification in advanced transportation systems using osprey and salp swarm optimized random forest model by Akshat Gaurav, Brij B. Gupta, Razaz Waheeb Attar, Ahmed Alhomoud, Varsha Arya, Kwok Tai Chui

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Design and Optimization of a Robust Wide‐Area Damping Controller for Mitigating Inter‐Area Oscillations in Wind‐Integrated Power Systems by Mehrdad Ahmadi Kamarposhti, Hassan Shokouhandeh, Sun‐Kyoung Kang, Ilhami Colak, El Manaa Barhoumi

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Enhancing student success prediction in higher education with swarm optimized enhanced efficientNet attention mechanism. by Meshari Alazmi, Nasir Ayub

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Evaluation of the effects of the body on athletes’ emotions and motivational behaviors from the perspective of big data public health by Qiang Zhang, Diandong Lian, Yiqiao Zhang

“…ObjectiveAn analysis was conducted on the impact of the body on athletes’ emotions and motivation from the perspective of Public Health (PH).MethodsPSO-KNN (Particle Swarm Optimization-K-Nearest Neighbor) algorithm and PSO-SVM algorithm (Particle Swarm Optimization-Support Vector Machine) were obtained by combining Particle Swarm Optimization (PSO), K-Nearest Neighbor (KNN), and Support Vector Machine (SVM), and then the recognition rates of the two algorithms were compared.ResultsWhen comparing the PSO-KNN algorithm and PSO-SVM algorithm on baseline removed and baseline not removed, the average recognition rates of PSO-KNN algorithm and PSO-SVM algorithm under emotional state were 56.66 and 54.75%, respectively. …”
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An Improved Soft Island Model of the Fish School Search Algorithm with Exponential Step Decay Using Cluster-Based Population Initialization by Liliya A. Demidova, Vladimir E. Zhuravlev

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Continuous prediction of knee joint angle in lower limbs based on sEMG: a method combining an improved ZOA optimizer and attention-enhanced GRU by Jian Lv, Binhao Huang, Ligang Qiang

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RL-QPSO net: deep reinforcement learning-enhanced QPSO for efficient mobile robot path planning by Yang Jing, Li Weiya

“…The RL-QPSO Net combines quantum-inspired particle swarm optimization (QPSO) and deep reinforcement learning (DRL) modules through a dual control mechanism to achieve path optimization and environmental adaptation. …”
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A multi objective optimization framework for smart parking using digital twin pareto front MDP and PSO for smart cities by Dinesh Sahu, Priyanshu Sinha, Shiv Prakash, Tiansheng Yang, Rajkumar Singh Rathore, Lu Wang

“…In response to these challenges, this paper proposes a Multi-Objective Optimization Framework for Smart Parking incorporating Digital Twin Technology, Pareto Front Optimization, Markov Decision Process (MDP), and Particle Swarm Optimization (PSO). …”
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Security-Enhanced Image Encryption: Combination of S-Boxes and Hyperchaotic Integrated Systems by Renjie Song, Haixia Zhao

“…In this paper, an image encryption method combining S-box and hyperchaotic integrated system is proposed. First, a particle swarm optimization algorithm is designed to search for S-boxes based on an adaptive function that takes into account several security metrics and an S-function inertia weighting strategy. …”
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Energy Optimization Strategy for Wind–Solar–Storage Systems with a Storage Battery Configuration by Yufeng Wang, Haining Ji, Runteng Luo, Bin Liu, Yongzi Wu

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Stochastic robot failure management in an assembly line under industry 4.0 environment by Kuldip Singh Sangwan, Anirudh Tusnial, Suveg V Iyer

“…This paper proposes an improved integrated model of operation reallocation and robot allocation for stochastic failures of a robotic assembly line. A particle swarm optimization (PSO) algorithm is developed to solve the proposed integrated model. …”
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Fault Location and Route Selection Strategy of Distribution Network Based on Distributed Sensing Configuration and Fuzzy C-Means by Bo Li, Guochao Qian, Lijun Tang, Peng Sun, Zhensheng Wu

“…To solve the problem of high cost and low efficiency of measuring equipment in traditional distribution network fault location, a fault section location and line selection strategy combining dynamic binary particle swarm optimization (DBPSO) configuration and fuzzy C-means (FCM) clustering is proposed in this paper. …”
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A Combined PSO-LSTM Prediction Model for Dam Deformation by HAO Ze-jia, SHI Yu-qun, CHENG Bo-chao, HE Jin-ping

“…By leveraging the long-short-term memory (LSTM) model and particle swarm optimization (PSO) algorithm from artificial intelligence technology, a combined PSO-LSTM dam deformation prediction model is established, offering a novel approach for enhancing the accuracy of dam deformation prediction. …”
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Communication‐awareness adaptive resource scheduling strategy for multiple target tracking in a multiple radar system by Yang Su, Ziyang Cheng, Zishu He, Minglong Deng

“…To tackle the resultant mixed‐integer, non‐convex, and non‐linear problem efficiently, incorporating with the proposed hybrid particle swarm optimization algorithm based on the Kullback–Leibler divergence, a two‐stage solution technique is developed to obtain the near‐optimal solution. …”
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