Research on over-the-horizon air combat guidance method based on dynamic RCS by SONG Shaomei, YU Yifei, LI Gai, YANG Qiming, ZHANG Jiandong

“…Then, to maximize the situation assessment value as the goal, particle swarm optimization algorithm is used to find the most appropriate overload at every moment, so as to guide our aircraft into the attack zone to constitute the launch conditions. …”
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Optimization of a Coupled Neuron Model Based on Deep Reinforcement Learning and Application of the Model in Bearing Fault Diagnosis by Shan Wang, Jiaxiang Li, Xinsheng Xu, Ruiqi Wu, Yuhang Qiu, Xuwen Chen, Zijian Qiao

“…By comparing the coupled neuron model optimized with a reinforcement learning algorithm, particle swarm algorithm, and quantum particle swarm algorithm, the experimental results show that the coupled neuron model optimized with a deep reinforcement learning algorithm has the optimal signal-to-noise ratio of the output signal and recognition rate of the bearing faults, which are −13.0407 dB and 100%, respectively. …”
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An Effective ABC-SVM Approach for Surface Roughness Prediction in Manufacturing Processes by Juan Lu, Xiaoping Liao, Steven Li, Haibin Ouyang, Kai Chen, Bing Huang

“…Further, to evaluate the optimization performance of ABC in parameters determination of SVM, this study compares the prediction performance of SVM models optimized by well-known evolutionary and swarm-based algorithms (differential evolution (DE), genetic algorithm (GA), particle swarm optimization (PSO), and ABC) and analyzes ability of these optimization algorithms from their optimization mechanism and convergence speed based on experimental datasets of turning and milling. …”
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Meteorological data implications modeling on evapotranspiration variability in arid and semi-arid zones in Saudi Arabia using hybrid metaheuristic by Oulad Naoui Noureddine, Sekkoum Mohamed, Cherif El Amine, Ali Alzaed, Meseret Abeje Gedfew, Sherif S. M. Ghoneim, Enas E. Hussein

“…In this paper, the Bat algorithm (BAT) with the Newton Method (NM), Bird Swarm Algorithm (BSA), Genetic Algorithm (GA), and Chicken Swarm Optimization Algorithm (CSO) are used as a hybrid model in arid and semi-arid zones in Saudi Arabia as well as for modeling rainfall, temperature, and solar radiation implications on evapotranspiration variability. …”
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Hybrid Feature-Based Disease Detection in Plant Leaf Using Convolutional Neural Network, Bayesian Optimized SVM, and Random Forest Classifier by Ashutosh Kumar Singh, SVN Sreenivasu, U.S.B. K. Mahalaxmi, Himanshu Sharma, Dinesh D. Patil, Evans Asenso

“…Binary particle swarm optimization plays a crucial role in hybrid feature selection; the purpose of this Algorithm is to obtain the suitable output with the least features. …”
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Kinematic Performance Analysis and Dimensional Optimization for 2PUS-PU Parallel Mechanism by Linxian Che, Jian Yi, Bing He, Xuedong Lin

“…A constrained optimization model is constructed to formulate the design problem of dimensional parameters on the maximizing radius of RTOW，and particle swarm optimization and differential evolution algorithm are adopted to solve this problem. …”
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Optimizing VGG16 deep learning model with enhanced hunger games search for logo classification by Mohammed Hussain, Thaer Thaher, Mohamed Basel Almourad, Majdi Mafarja

“…The Hunger Games Search (HGS) is a recent swarm intelligence algorithm that has shown good performance across various applications. …”
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Gaussian barebone mechanism and wormhole strategy enhanced moth flame optimization for global optimization and medical diagnostics. by Jingjing Ma, Zhifang Zhao, Lin Zhang

“…Moth Flame Optimization (MFO) is a swarm intelligence algorithm inspired by the nocturnal flight mode of moths, and it has been widely used in various fields due to its simple structure and high optimization efficiency. …”
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Enhancing education quality with hybrid clustering and evolutionary neural networks in a multi phase framework by Saleem Malik, Chandrakanta Mahanty, Jnanaranjan Mohanty, Krunal Vaghela, T. Narmadha, R. Sivaranjani, Javed Khan Bhutto, Saiful Islam, Anwar Khan, Amanuel Zewdie

“…The NeuroEvoClass algorithm mixes evolutionary strategies inspired by swarm intelligence and artificial neural networks (ANN) to improve student performance prediction in Phase II. …”
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Binary atom search optimisation approaches for feature selection by Jingwei Too, Abdul Rahim Abdullah

“…In the experiment, the BASO with an optimal transfer function that contributes to the best classification performance is presented. The particle swarm optimisation (PSO), binary differential evolution (BDE), binary bat algorithm (BBA), binary flower pollination algorithm (BFPA), and binary salp swarm algorithm (BSSA) are used to evaluate the efficacy and efficiency of proposed approaches in feature selection. …”
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Microgrid system for electric vehicle charging stations integrated with renewable energy sources using a hybrid DOA–SBNN approach by Kommoju Naga Durga Veera Sai Eswar, M. Arun Noyal Doss, Mohammad Shorfuzzaman, Ali Elrashidi

“…The proposed method outperforms all current techniques, including the Multi swarm Optimization (MSO), the Multi-Objective Gray Wolf Optimizer (MOGWO), and the Modified Multi-objective Salp Swarm Optimization algorithm (MMOSSA). …”
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A Pareto-Based Clustering Approach for Solving a Bi-Objective Mobile Hub Location Problem with Congestion by Maryam Dehghan Chenary, Arman Ferdowsi, Richard F. Hartl

“…<i>Results</i>: Various experiments have been conducted on the Australian Post dataset to evaluate the proposed method. The results have been compared with Multiple-Objecti-ve Particle Swarm Optimization (MOPSO) and Non-Domi-nated Sorting Genetic Algorithm (NSGA-II) using several performance evaluation metrics. …”
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Comparative Analysis of Bio-Inspired Enhancement Techniques for Localization in 2D Wireless Sensor Networks by Rabhi Seddik

“…This study conducts a comparative evaluation of three bio-inspired optimization algorithms for node localization: Particle Swarm Optimization (PSO), Fruit Fly Optimization Algorithm (FOA), and Drop Mongoose Optimization Algorithm (DMOA). …”
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Challenges of International Trade and Government Governance from the Perspective of Economic Globalization by Dan Ge

“…On the basis of expounding the particle swarm optimization algorithm and GMDH algorithm, the optimization mode, method, and process of GMDH network based on particle swarm optimization are also expounded. …”
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AMBWO: An Augmented Multi-Strategy Beluga Whale Optimization for Numerical Optimization Problems by Guoping You, Zengtong Lu, Zhipeng Qiu, Hao Cheng

“…Beluga whale optimization (BWO) is a swarm-based metaheuristic algorithm inspired by the group behavior of beluga whales. …”
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Radio frequency energy harvesting-combined collaborative energy-saving computation offloading mechanism by Bei TANG, Qian WANG, Siguang CHEN

“…In order to fit the differentiated energy demands in vertical markets and ensure that internet of things (IoT) devices can hold an efficient and sustainable operation mode, a radio frequency energy harvesting-combined collaborative energy-saving computation offloading mechanism was studied.Specifically, a system energy consumption minimization problem was formulated under the joint optimization consideration of computation offloading decision, uplink bandwidth resource allocation, downlink bandwidth resource allocation and base station power splitting.Meanwhile, by combining the concept of penalty function, a new evaluation index was introduced, and then an adaptive particle swarm optimization-based collaborative energy saving computation offloading (APSO-CESCO) algorithm was proposed to solve the problem.The proposed algorithm constructed dynamic inertia weight and linearly adjusted penalty factor, which could alternate the spatial distribution density of the particle community in real-time during the iterative search process, and the optimal computation offloading policy with tolerable punishment could be well-generated.Furthermore, to prevent particles from exceeding exploration range, the velocity boundary was introduced which could also reduce the generation probability of invalid solutions and improve the actual exploration effectiveness.Finally, the simulation results show that the proposed algorithm can achieve higher convergence efficiency and solution accuracy, and compared with other common benchmark schemes, the system energy consumption can be reduced by 34.09%, 14.72%, and 6.86%, respectively.…”
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Blasting vibration velocity prediction of open pit mines based on GRA-EPSO-SVM model by Pengfei ZHANG, Yong YUAN, Yunhua HE, Shaojun DAI, Jiazhen LI, Xuehai CHI, Wei LI, Xue SUN, Jiao ZHANG, Runcai BAI, Honglu FEI

“…The peak value of blasting vibration in open pit mine is the main index to evaluate blasting effect. In the scene of coal and rock interbedded blasting in open-pit mine, aiming at the problems that the existing prediction methods of blasting vibration peak value are difficult to achieve ideal prediction results, resulting in unreasonable design of blasting parameters and initiation network, a prediction model of blasting vibration peak value based on integrated particle swarm optimization support vector machine algorithm (GRA-EPSO-SVM) with grey correlation degree feature selection is proposed. …”
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Research on Damage Identification of Nonuniform Microcrack in Beam Structures by Jia Guo, Deqing Guan, Yanran Pan

“…The singularity of the wavelet coefficient can be used to identify the signal singularity quickly and accurately, and IA efficiently and accurately calculates the structural damage severity. The particle swarm optimization (PSO) algorithm and the genetic algorithm (GA), widely used, are applied to identify the damage severity of the beam. …”
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Neuro-evolutionary models for imbalanced classification problems by Israa Al-Badarneh, Maria Habib, Ibrahim Aljarah, Hossam Faris

“…The utilized algorithms are the Grey Wolf Optimization (GWO), Particle Swarm Optimization (PSO), and the Salp Swarm Algorithm (SSA). …”
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Optimization of household medical waste recycling logistics routes: Considering contamination risks. by Jihui Hu, Ying Zhang, Yanqiu Liu, Jiaqi Hou, Aobei Zhang

“…The complexity inherent in the optimization problem has motivated the development of the Adaptive Hybrid Artificial Fish Swarming Algorithm with Non-Dominated Sorting (AH-NSAFSA). …”
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