Synthesis of the Spatial Arrangement of Magnetic Field Sensors for Active Magnetic Field Shielding Systems of Overhead Power Lines by Kuznetsov B.I., Nikitina T.B., Bovdui I.V., Voloshko O.V., Kolomiets V.V., Kobylianskyi B.B.

“…Solution of the minimax vector optimization problem, calculated on the basis of optimization algorithms for a multi-swarm of particles from Pareto-optimal solutions, taking into account the parameters of binary relations. …”
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Experimental realization of PSO-based hybrid adaptive sliding mode control for force impedance control systems by Sarucha Yanyong, Somyot Kaitwanidvilai

“…A sliding surface guarantees system stability, while Particle Swarm Optimization (PSO) optimizes impedance parameters, reducing the risk of local minima. …”
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Multi-head surface mounting placement optimisation based on adaptive multi-point crossover operator by Song Zhiqiang, Zhang Chunfu

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A precise ultra high frequency partial discharge location method for switchgear based on received signal strength ranging by Jiajia Song, Jinbo Zhang, Xinnan Fan

“…To further improve positioning accuracy, the convergence conditions of the particle swarm optimization are investigated, and, considering their constraints, an improved particle swarm optimization algorithm is proposed. …”
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Evaluation Model of Low-Carbon Circular Economy Coupling Development in Forest Area Based on Radial Basis Neural Network by Chang Liu

“…In this paper, we study the radial neural network algorithm for low-carbon circular economy in forest area, design a coupled development evaluation model, study its algorithmic ideas operation mode and the update formula obtained by standard algorithm, and finally optimize the RBF neural network by particle swarm algorithm. …”
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A non-line-of-sight error mitigation method for location estimation by Chien-Sheng Chen

“…The proposed algorithm uses the intersections of three time-of-arrival circles based on the particle swarm optimization technique to give a location estimation of the mobile station in non-line-of-sight environments. …”
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A High-Precision Real-Time Temperature Acquisition Method Based on Magnetic Nanoparticles by Yuchang Zhu, Li Ke, Yijing Wei, Xiao Zheng

“…Additionally, under dual-frequency superimposed magnetic field excitation, a higher temperature inversion accuracy is achieved compared with that of the particle swarm optimization–gray wolf optimization algorithm, reducing the error from 0.237 K to 0.094 K.…”
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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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基于粒子群优化的形态学滤波器消噪方法 by 吴国洋

“…Aiming at removing the noise of the vibration signal,a new mathematical morphological filter method is proposed,the proposed filter is optimized by particle swarm optimization algorithm.Firstly,the morphological filter is constructed according to the characteristic of morphological algorithm.Then,the particle swarm optimization algorithm is used to select the adaptive structural element,which has an important role in morphological filter,and the maximum signal-noise-ratio is used as the criteria of the optimization process,achieving to get the optimal structural element.Finally,the simulation experiment and the bearing fault signal are analyzed,the results show that the optimal morphological filter is better in removing the noise than the wavelet method and the traditional morphological filter methods,the proposed method can effectively reduce the noise of the mechanical equipment.…”
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Multimode Resource-Constrained Multiple Project Scheduling Problem under Fuzzy Random Environment and Its Application to a Large Scale Hydropower Construction Project by Jiuping Xu, Cuiying Feng

“…Then a combinatorial-priority-based hybrid particle swarm optimization algorithm is developed to solve the proposed model, where the combinatorial particle swarm optimization and priority-based particle swarm optimization are designed to assign modes to activities and to schedule activities, respectively. …”
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Fault Diagnosis of Gearbox based on Multi-fractal and PSO-SVM by Li Sha, Pan Hongxia, Zhang Jundong, Zhao Weiwei

“…Aiming at the non-stationary and nonlinear of gearbox vibration signals,a fault diagnosis method based on the multi-fractal and particle swarm optimization support vector machine（PSO-SVM）is put forward.Firstly,the fractal filter with short-time fractal dimension as fuzzy control parameters is used to filtering noise reduction the gearbox vibration signals with bigger background noises.Secondly,the multi-fractal spectrum algorithm is applied to analyze the signal after filtering,the results show that the characteristic parameters:Δa（q）、f（a（q））maxand box dimensions Dbcan give a good presentation for gearbox working condition.Finally,the particle swarm optimization（PSO）is applied to optimize the parameters of support vector machine（SVM）.Taking the multi-fractal characteristic vectors as input parameters of PSO-SVM and SVM to recognize the fault types of the gearbox.The results show that SVM based on particle swarm optimization can improve the classification accuracy.Meanwhile,the validity of gearbox fault diagnosis based on muti-fractal and PSO-SVM is proved.…”
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Classification Prediction of Rockburst in Railway Tunnel Based on Hybrid PSO-BP Neural Network by Min Zhang

“…Then, the BP neural network is improved by using particle swarm optimization (PSO) combined with the simulated annealing algorithm. …”
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基于模拟退火粒子群算法的圆柱齿轮减速器的可靠性优化 by 郑严, 程文明, 程跃, 吴晓

“…Simulate anneal-particle swarm optimization（SA-PSO） is a simple and efficient stochastic global optimization algorithm,and simulated annealing is involved into particle swarm optimization（PSO） with Crossover and Gaussian mutation.The reliability optimization model maximize reducer driven system is established by combining the SA-PSO with the theory of reliability optimization design,and the reliability optimization method for cylindrical gear reducer is presented on the basis of the SA-PSO.This optimization method is used to optimize a cylindrical gear reducer,and the optimal results are much better than those by the PSO,the mixed penalty function method and the traditional design method.The example shows that this reliability optimization design method is effective,and has the predominant capability of global optimization and convergence precision.Moreover,it has a certain reference significance for other mechanical parts reliability optimization.…”
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Adaptive Neural Network Iterative Sliding Mode Course Tracking Control for Unmanned Surface Vessels by Chunbo Zhao, Huaran Yan, Deyi Gao, Renqiang Wang, Qinrong Li

“…The performance experiment verifies the effectiveness and practicability of the adaptive iterative sliding mode control algorithm for unmanned surface ships based on reinforcement learning and particle swarm optimization algorithm; meanwhile, comparative tracking experiments verify that the comprehensive performance of the proposed USV’s course tracking control system is better than that of the genetically optimized neural network sliding mode control system. …”
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State-Aware Energy Management Strategy for Marine Multi-Stack Hybrid Energy Storage Systems Considering Fuel Cell Health by Pan Geng, Jingxuan Xu

“…A hybrid Genetic Algorithm–Particle Swarm Optimization (GA-PSO) approach achieves global optimization. …”
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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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Study on Fault Arc Recognition Based on Back-Propagation Neural Network by QIAO Weide

“…Frequency doubling wavelet analysis is applied to extract the characteristics of fault arc signal. Vector, firefly-particle swarm optimization algorithm is used to optimize the initial structure parameters of BP neural network. …”
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Research on Damage Identification of Nonuniform Microcrack in Beam Structures by Jia Guo, Deqing Guan, Yanran Pan

“…The results show that the wavelet-particle swarm optimization (WPSO) and the wavelet-genetic algorithm (WGA) can accurately and efficiently identify the structural semielliptical damage location and severity and that these methods are not easily influenced by noise. …”
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A Predictive Analysis of the Business Environment of Economies along the Belt and Road Using the Fractional-Order Grey Model by Lingling Pei, Jun Liu

“…This paper determined the optimal order of FGM (1, 1) model through particle swarm optimization algorithm and combined with the World Bank business environment data to predict and analyze the business environment of economies along the Belt and Road. …”
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基于混合蛙跳算法的齿轮传动优化设计 by 何兵, 车林仙, 刘初升

“…The hybrid optimization algorithm（HODEFL） overcame the disadvantages on low precision and premature convergence of shuffled frog leaping algorithm（SFLA） for high-dimensional optimization by taking advantages of strong global search and rapid convergence of DE/best/2/bin（DEb2） in differential evolution algorithm（SDE）.The SFLA and DE are hybridized to form a hybrid optimization algorithm（HODEFL） in order to overcome the disadvantages of the SFLA.The study object is the optimization design of the cylindrical helical gear reducer,establishing minimum volume.By comparing with the improved particle swarm optimization（LWPSO）,SFLA and with DEb2 evolutionary algorithm,the HODEFL algorithm is superior to other three algorithms in terms of optimization efficiency,computational accuracy and robustness.…”
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