Results 261 to 270 of about 248,257 (327)
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IEEE Transactions on Transportation Electrification, 2021
To overcome the limitations that active disturbance rejection control (ADRC) system of a bearingless induction motor (BIM) has difficulty in tuning parameters depending on experience to select parameters, an ADRC strategy based on improved particle swarm
Zebin Yang +4 more
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To overcome the limitations that active disturbance rejection control (ADRC) system of a bearingless induction motor (BIM) has difficulty in tuning parameters depending on experience to select parameters, an ADRC strategy based on improved particle swarm
Zebin Yang +4 more
semanticscholar +1 more source
IEEE Transactions on Instrumentation and Measurement, 2021
An improved particle swarm optimization method with multistage inertia weights is proposed for the design of gradient coils for use in magnetocardiography systems.
Fengwen Zhao +3 more
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An improved particle swarm optimization method with multistage inertia weights is proposed for the design of gradient coils for use in magnetocardiography systems.
Fengwen Zhao +3 more
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Computers & Operations Research, 2020
The flexible job shop scheduling problem (FJSP) is a typical scheduling problem in practical production and has been proven to be a NP-hard problem. The study of FJSP is important to remarkably direct actual manufacturing processes. The paper proposes an
Haojie Ding, Xingsheng Gu
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The flexible job shop scheduling problem (FJSP) is a typical scheduling problem in practical production and has been proven to be a NP-hard problem. The study of FJSP is important to remarkably direct actual manufacturing processes. The paper proposes an
Haojie Ding, Xingsheng Gu
semanticscholar +1 more source
An improved particle swarm optimization algorithm
2008 IEEE International Conference on Granular Computing, 2008An improved Particle Swarm Optimization (IPSO) algorithm is proposed in this paper. In the algorithm, a premature estimate mechanism is introduced to judge whether the particles accumulate in a small region and tell the probability whether the swarm is trapped in a local optimum.
Ping Luo +3 more
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Improved Particle Swarm Optimization algorithms for electromagnetic optimization
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology, 2008Particle Swarm is a relatively novel approach for global stochastic optimization. In this paper some variations over the basic algorithm are proposed, with the aim of a more efficient search over the solution space obtained with a negligible overhead in both complexity and speed. The presented algorithms are then applied to a mathematical test function
MUSSETTA, MARCO +4 more
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Improvement of Particle Swarm Optimization
PIERS Online, 2009A new technique titled \Particle Refresh" and a hybridization with conjugate gradient method are introduced to particle swarm optimization (PSO). The former charges power to inactive particle to improve the recovery ability of PSO after trapping on a local solution, and as a result, it becomes easy to choose suitable values for control-parameters to ...
K. Kawakami, Zhi Qi Meng
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Improved heterogeneous particle swarm optimization
Journal of Information and Optimization Sciences, 2017In this paper, we propose an improved heterogeneous particle swarm optimization (IHPSO) with enhanced exploration and exploitation.
Djalil Boudjehem, Badreddine Boudjehem
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Computers & Operations Research, 2020
This paper addresses the multi-stage hybrid flowshop scheduling problem with identical parallel machines at each stage by considering the effect of human factors. The various levels of labours and the effects of their learning and forgetting are studied.
M. K. Marichelvam +2 more
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This paper addresses the multi-stage hybrid flowshop scheduling problem with identical parallel machines at each stage by considering the effect of human factors. The various levels of labours and the effects of their learning and forgetting are studied.
M. K. Marichelvam +2 more
semanticscholar +1 more source
Improved Particle Swarm Optimization Algorithm
2010 International Conference on Computational Intelligence and Software Engineering, 2010Particle Swarm Optimization (PSO) is a new random computational method for tackling optimization functions. However, it is easily trapped into the local optimum when solving the complexity and high-dimensional problems, which makes the performance of PSO greatly reduced.
Ye Gao, Shan Li
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Applied Soft Computing, 2020
The highlight of this paper is to propose an innovative approach to compute an optimal collision free trajectory path for each robot in a known and complex environment.
P. K. Das, P. Jena
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The highlight of this paper is to propose an innovative approach to compute an optimal collision free trajectory path for each robot in a known and complex environment.
P. K. Das, P. Jena
semanticscholar +1 more source