Acoustic Signal Aided Detection Method of Spiral Bevel Gears Based on PSO-MCKD by Li Xianshan, Tian Yu, Wei Lilin, Zhao Xiaofeng, Yan Changfeng

“…Combined with the particle swarm optimization(PSO) algorithm and the maximum correlated kurtosis deconvolution(MCKD) based signal processing methods, the effect of different axial deviations on the gear mesh acoustic signals is investigated. …”
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Trajectory Tracking of a Flexible Robot Manipulator by a New Optimized Fuzzy Adaptive Sliding Mode-Based Feedback Linearization Controller by M. J. Mahmoodabadi, N. Nejadkourki

“…Finally, a multiobjective particle swarm optimization algorithm is used to find the optimum fuzzy rules. …”
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Inverse Kinematics and Reachable Workspace of UPS/UPR/SP Parallel Mechanism by Longfei Li, Yaohong Zhao, Bin Sun, Ruiqin Li, Guowang Pang

“…Firstly，the degree of freedom of UPS/UPR/SP parallel mechanism is analyzed by using screw theory，and the degree of freedom of the mechanism is analyzed and verified based on the improved Kutzbach-Grübler formula； then，particle swarm optimization （PSO） algorithm and closed vector method are used to solve the forward and inverse solutions of the mechanism，and the reachable workspace of the mechanism is solved by using the limit search method in Matlab software； Finally，the mechanism is applied to the express sorting with high accuracy of position accumulation. …”
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Federated learning resource management for energy-constrained industrial IoT devices by Shaoshuai FAN, Jianbo WU, Hui TIAN

“…Given the impact of limited wireless resources, a dynamic multi-dimensional resource joint management algorithm was proposed, which intended to tackle the problem of device failure and training interruption caused by the limited battery energy in federated learning network in industrial Internet of things (IIoT).Firstly, the optimization problem was decoupled into battery energy allocation, equipment resource allocation and communication resource allocation sub-problems which were interdependent with the goal of maximizing the fixed-time learning accuracy.Then, the equipment transmission and computing resource allocation problem were solved based on particle swarm optimization algorithm under the given energy budget.Thereafter, the resource block iterative matching algorithm was proposed to optimize the optimal communication resource allocation strategy.Finally, the online energy allocation algorithm was proposed to adjust the energy budget allocation.Simulation results validate the proposed algorithm can improve the model learning accuracy compared with other benchmarks, and can perform better in energy shortage scenarios.…”
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A Comparison of Metaheuristic Techniques for Solving Optimal Sitting and Sizing Problems of Capacitor Banks to Reduce the Power Loss in Radial Distribution System by Tongfei Lei, Saleem Riaz, Hira Raziq, Munira Batool, Feng Pan, Jianfeng Wang

“…In this paper, several metaheuristic techniques such as particle swarm optimization (PSO), Harmony search, Bat, Cuckoo, and Grey-wolf (GW) algorithms are employed to find the size of capacitor banks. …”
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An Improved Test Selection Optimization Model Based on Fault Ambiguity Group Isolation and Chaotic Discrete PSO by Xiaofeng Lv, Deyun Zhou, Yongchuan Tang, Ling Ma

“…The improved chaotic discrete particle swarm optimization (PSO) algorithm is adopted to solve the improved test selection optimization model. …”
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Vibration Fatigue Life Prediction and Parameter Optimization of Roadheader Picks by He Yang, Li Xiaohuo, Xi Yabing

“…The corner of the pick is defined as the optimization objective based on particle swarm optimization algorithm, the optimal corner value is obtained, and the life of the picks is increased by an order of magnitude. …”
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FAULT DIAGNOSIS METHOD OF AIRBORNE FUEL PUMP BASED ON CEEMD SHANNON ENTROPY AND GAPSO-SVM by BAO Jie, JING Bo, JIAO XiaoXuan, ZHANG QingYi, ZHANG Yu

“…Compared with BP neural network, SVM optimized by particle swarm optimization（PSO） and SVM optimized by genetic algorithm（GA）, the results showed that the model of SVM diagnosis optimized by GA has the advantages of fast training, high accuracy and short time-effect, and it has good engineering application value.…”
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Energy-efficient resource allocation method in mobile edge network based on double deep Q-learning by Peng YU, Junye ZHANG, Wenjing LI, Fanqin ZHOU, Lei FENG, Shu FU, Xuesong QIU

“…To improve the system energy efficiency in mobile edge networks, a resource allocation method based on double deep Q-learning(DDQL) for integration of communication, computing, storage resources was proposed for the downlink communication process under the network architecture of multiple tasks, end devices, edge gateways and edge servers.A resource allocation model was constructed, which took the minimization of average energy consumption of tasks as the optimization goal and set the constraints of task delay limits and communication, computing, and storage resource limits.According to the model characteristics, a suitable resource allocation model and method based on DDQL framework was proposed to make intelligent allocation decisions for communication and computing resources and allocate storage resources on demand.Simulation results show that the proposed DDQL-based solution can effectively solve the multi-task resource allocation problem with good converge and low time complexity, and it reduces the average energy consumption of tasks by at least 5% compared with the solving methods based on random algorithm, greedy algorithm, particle swarm optimization algorithm and deep Q-learning while ensuring the quality of service.…”
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A Dynamic Multistage Hybrid Swarm Intelligence Optimization Algorithm for Function Optimization by Daqing Wu, Jianguo Zheng

“…In the third stage, we make use of the particle swarm optimization global model, which has a faster convergence speed to enhance the global convergence in solving the whole problem. …”
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Predictive Differential Game Guidance Approach for Hypersonic Target Interception Based on CQPSO by Fan He, Weiyi Chen, Yang Bao

“…The Chaotic Quantum Particle Swarm Optimization (CQPSO) algorithm is utilized to address the nonlinear differential game problem to generate the instantaneous and predicted guidance commands for the interceptor and target. …”
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Studies on Pumice Lightweight Aggregate Concrete with Quarry Dust Using Mathematical Modeling Aid of ACO Techniques by J. Rex, B. Kameshwari

“…Here, the modeling is carried out with three different optimization techniques like genetic algorithm (GA), particle swarm optimization (PSO), and ant colony optimization (ACO) with 80% of data from experiment utilized for the training and the remaining 20% for the validation. …”
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Dynamic Performance Analysis of Semiactive Vehicle ISD Suspension Based on the Power-Driven-Damper Strategy by Yujie Shen, Jinsen Wang, Fu Du, Xiaofeng Yang, Yanling Liu, Long Chen

“…Then, the parameters of the two models are optimized by the particle swarm optimization algorithm, and the optimization results show that the suspension S3 has better performance. …”
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Soft Sensor for Oxide Scales on the Steam Side of Superheater Tubes under Uneven Circumferential Load by Qing Wei Li, Gui Huan Yao

“…At last, the oxide scale thickness and stress sensors are established on support vector machine (SMV) optimized by particle swarm optimization (PSO) with time and circumferential angles as inputs and oxide scale thickness and stress as outputs. …”
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Frequency Diverse Array Target Localization Based on IPSO-BP by Qinghua Liu, Kai Ding, Bingsen Wu, Quanmin Xie

“…The improved particle swarm optimization (IPSO) algorithm with nonlinear weights is developed to optimize the neural network weights and biases to prevent BP neural network from easily falling into local minimum points. …”
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Cell on Wheels-Unmanned Aerial Vehicle System for Providing Wireless Coverage in Emergency Situations by Hazim Shakhatreh, Khaled Hayajneh, Khaled Bani-Hani, Ahmad Sawalmeh, Muhammad Anan

“…We utilize the exhaustive search (ES) and particle swarm optimization (PSO) algorithms to solve the optimization problem. …”
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Improved Population Intelligence Algorithm and BP Neural Network for Network Security Posture Prediction by Yueying Li, Feng Wu

“…First, the adaptive adjustment of the two parameters with the increase of iterations is achieved by improving the inertia weights and learning factors in the particle swarm optimization (PSO) algorithm so that the PSO has a large search range and high speed at the initial stage and a strong and stable convergence capability at the later stage. …”
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Research on indoor THz channel reflection and transmission characteristics for integrated sensing and communication by LIAO Xi, LIN Changxi, ZHENG Xiangquan, WANG Yang, LIN Feng, CHEN Qianbin

“…Measurement campaigns were carried out on seven indoor materials at 130~134 GHz using a vector network analyzer-based measurement platform, and the frequency dependence and incidence angle dependence of the terahertz channel reflection and transmission characteristics were analyzed, which were compared with the measurement results at 282~290 GHz, to have the reflection loss characteristics in the two frequency bands revealed. A quantum particle swarm optimization algorithm was used to extract the material electromagnetic parameters, and a joint frequency-incidence angle model of the reflection coefficient was proposed. …”
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A Hybrid Swarm Intelligence Algorithm for Intrusion Detection Using Significant Features by P. Amudha, S. Karthik, S. Sivakumari

“…To deal with this problem, in this paper a hybrid algorithm is proposed to integrate Modified Artificial Bee Colony (MABC) with Enhanced Particle Swarm Optimization (EPSO) to predict the intrusion detection problem. …”
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FAULT DIAGNOSIS METHOD OF SUBMERSIBLE SEWAGE PUMP BASED ON IMPROVED HOPFIELD NEURAL NETWORK by WANG Hui, LI NanQi, YANG ZhiPeng, ZHAO GuoChao, TIAN LiYong

“…The connection weights of HNN neural network were optimized by particle swarm optimization（PSO） algorithm to improve the global convergence ability of the improved neural network, and the improved HNN neural network model was obtained. …”
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