Parameter Design and Performance Optimization of Aerostatic Bearing by YANG Chunmei, CAO Bingzhang

“…In this paper, problems such as loadcarrying capacity, low stiffness, and vibration caused by large volume flow rate of aerostatic bearing has been studied In order to solve these problems, the particle swarm optimization algorithm is used to optimize the key parameters of throttle orifice on aerostatic bearing The simplified twodimensional Reynolds equation is solved by finite element method and the mathematical model is built Based on this model, the main performance parameters such as loadcarrying capacity, stiffness and volume flow rate of aerostatic bearing are calculated The coupling relationship between the structural dimension parameters which determining the main performance of aerostatic bearing is analyzed The multiobjective optimization design of the structural dimension parameters is carried out by particle swarm optimization With the simulation calculation of the aerostatic bearing, the loadcarrying capacity, stiffness, volume flow rate and other relevant performances are calculated The main performance of the optimized aerostatic bearing is compared with the original data The results show that compared with the performance before optimization, the loadcarrying capacity, stiffness of the aerostatic bearing are increased by 17%, 363% and the volume flow rate is decreased by 434% And the problems such as low loadcarrying capacity, low stiffness, and vibration caused by large volume flow rate of aerostatic bearing has been solved…”
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SOLVING ENGINEERING OPTIMIZATION PROBLEMS WITH THE SWARM INTELLIGENCE METHODS by A. V. Panteleev, M. D. Evdokimova

“…Such methods include the methods of Swarm Intelligence: spiral dynamics algorithm, stochastic diffusion search, hybrid seeker optimization algorithm. …”
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Enhancing crane and gate OCR efficiency at container terminal using a hybrid genetic algorithm and neural network model: case study of tangier med port by Hamza Garmouch, Otman Abdoun

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PSO-Based Robust Control of SISO Systems with Application to a Hydraulic Inverted Pendulum by Michael G. Skarpetis, Nikolaos D. Kouvakas, Fotis N. Koumboulis, Marios Tsoukalas

“…In the second stage, a Particle Swarm Optimization Algorithm (PSO) is applied to find suboptimal solutions for the controller parameters in these regions, with respect to a suitable performance cost function. …”
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Portfolio optimization with MOPSO-Shrinkage hybrid model by Minh Tran, Nhat M. Nguyen

“…This paper introduces a novel framework for portfolio optimization that integrates Multi-Objective Particle Swarm Optimization (MOPSO) with shrinkage covariance estimators, referred to as the MOPSO-Shrinkage hybrid model. …”
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Bearing Fault Diagnosis in the Mixed Domain Based on Crossover-Mutation Chaotic Particle Swarm by Tongle Xu, Junqing Ji, Xiaojia Kong, Fanghao Zou, Wilson Wang

“…Finally, the support vector machine is optimized using the improved chaotic particle swarm to improve fault classification diagnosis. …”
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A resource allocation algorithm based on improved salp swarm algorithm in cognitive smart grid by SHEN Hongting

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STUDY ON CALCULATION METHOD OF STRESS SEPARATION BY OBLIQUE INCIDENCE TECHNIQUE by LIU XiaoMeng, DAI ShuGuang

“…Conventional method for solving nonlinear overdetermined equations is difficult,new particle swarm optimization algorithms are proposed for oblique incidence stress separation. …”
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Hierarchical Swarm Model: A New Approach to Optimization by Hanning Chen, Yunlong Zhu, Kunyuan Hu, Xiaoxian He

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Multidimensional water-economic-ecological joint optimization for Manas River Basin, China, using a dual-population co-evolutionary algorithm by Jian Qin, Yongpeng Tong, Muhammad Arsalan Farid, Heng Zhang, Hao Tian, Xiaolong Li, Xinlin He, Lianqing Xue, Yi Li, Yongli Gao, Guang Yang

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Internal Optimization Stochastic Model of Virtual Power Plant Participating in Gas and Electricity Market by Yuanyuan PENG, Renjun ZHOU, Ziqi ZENG, Jian FENG, Yuanlin CHENG, Shaofeng FANG

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Optimizing Route Planning via the Weighted Sum Method and Multi-Criteria Decision-Making by Guanquan Zhu, Minyi Ye, Xinqi Yu, Junhao Liu, Mingju Wang, Zihang Luo, Haomin Liang, Yubin Zhong

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An Effective Routing Algorithm to Minimize the UAV Routing Time and Extend the Network Lifetime in Clustered IoT Network by H. Zafor, T. A. Sheikh, N. Mazumdar, A. Nag

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An Intelligent Inspection and Scheduling Algorithm for Integrated Pipe Gallery Based on Cloud Robot by ZHOU Xiwei, SHANG Xiao, SHANG Xinjuan, YAN Maode, WANG Fafa

“…In order to solve the problem of multiple iterations and poor real-time performance, it proposed an improved adaptive weight particle swarm optimization-genetic hybrid optimization algorithm combined with particle swarm optimization and genetic algorithm. …”
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On efficiency of methods and algorithms for solving optimization problems considering objective function specifics by E. N. Ostroukh, Yu. O. Chernyshev, L. N. Evich, P. A. Panasenko

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ICSO: A Novel Hybrid Evolutionary Approach with Crisscross and Perturbation Mechanisms for Optimizing Generative Adversarial Network Latent Space by Zhihui Chen, Ting Lan, Zhanchuan Cai, Zonglin Liu, Renzhang Chen

“…By combining the global and local search capabilities of particle swarm optimization (PSO) with the rapid convergence of crisscross optimization, ICSO efficiently explores and exploits the latent space. …”
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An optimal control method considering degradation and economy based on mutual learn salp swarm algorithm of an islanded zero‐carbon DC microgrid by Ying Han, Yujing Hou, Luoyi Li, Weifeng Meng, Qi Li, Weirong Chen

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Enhanced Unmanned Surface Vehicle Path Planning Based on the Pair Barracuda Swarm Optimization Algorithm: Implementation and Performance in Thousand Island Lake by Binghua Shi, Zeyu Liu, Zhou He, Chen Wang, Jia Guo

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Random Walk‐Based GOOSE Algorithm for Solving Engineering Structural Design Problems by Sripathi Mounika, Himanshu Sharma, Aradhala Bala Krishna, Krishan Arora, Syed Immamul Ansarullah, Ayodeji Olalekan Salau

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Enhancing Energy Efficiency in IoT-WSNs Through Optimized PSO Cluster Head Selection by Muhammad Haris, Haewoon Nam

“…This paper proposes a particle swarm optimization (PSO) based clustering algorithm that incorporates a double-exponential adaptive inertia weight update to balance global exploration and local exploitation dynamically. …”
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