Results 211 to 220 of about 28,590 (257)

Chaotic Inertia Weight in Particle Swarm Optimization

Second International Conference on Innovative Computing, Informatio and Control (ICICIC 2007), 2007
The inertia weight is one of the parameter in particle swarm optimization algorithm. It gets important effect on balancing the global search and the local search in PSO. Basing on the linear descending inertia weight and the random inertia weight, this paper presents the strategy of chaotic descending inertia weight and the strategy of chaotic random ...
Yong Feng, Gui-Fa Teng, Ai-Xin Wang, Yong-Mei Yao   +3 more
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Particle Swarm Optimization with Probabilistic Inertia Weight

2018
Particle swarm optimization (PSO) is a stochastic swarm-based algorithm inspired by the intelligent collective behavior of some animals. There are very few parameters to adjust in PSO which makes PSO easy to implement. One of the important parameter is inertia weight (ω) which balances the exploration and exploitation properties of PSO in a search ...
Ankit Agrawal, Sarsij Tripathi
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Selective Effects of Weight and Inertia on Maximum Lifting

International Journal of Sports Medicine, 2012
A novel loading method (loading ranged from 20% to 80% of 1RM) was applied to explore the selective effects of externally added simulated weight (exerted by stretched rubber bands pulling downward), weight+inertia (external weights added), and inertia (covariation of the weights and the rubber bands pulling upward) on maximum bench press throws.
B, Leontijevic, N, Pazin, M, Kukolj, D, Ugarkovic, S, Jaric   +4 more
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Inertia weight control strategies: Particle roaming behavior

2017 IEEE 4th International Conference on Soft Computing & Machine Intelligence (ISCMI), 2017
The performance of particle swarm optimization (PSO) algorithms have shown to be very sensitive to the main control parameters. Due to this sensitivity, various approaches have been developed to dynamically adjust the value of these control parameters in an attempt to remove the necessity of prior control parameter tuning.
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Inertia weight strategies in Multiswarm Particle swarm Optimization

2020 4th International Conference on Advanced Systems and Emergent Technologies (IC_ASET), 2020
The Particle Swarm Optimization (PSO) algorithm is widely applied in several areas of activity, namely image processing, modeling and system identification. To improve the search performance of this algorithm, several strategies have been used at this level. Among these are the MSPSO (Multiswarm Particle Swarm Optimization) algorithm. On the other hand,
Sami Zdiri, Jaouher Chrouta, Abderrahmen Zaafouri   +2 more
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Inertia weight control strategies for particle swarm optimization

Swarm Intelligence, 2016
Particle swarm optimization (PSO) is a population-based, stochastic optimization technique inspired by the social dynamics of birds. The PSO algorithm is rather sensitive to the control parameters, and thus, there has been a significant amount of research effort devoted to the dynamic adaptation of these parameters. The focus of the adaptive approaches
Kyle Robert Harrison, Andries P. Engelbrecht, Beatrice M. Ombuki-Berman   +2 more
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Particle swarm optimization with selective multiple inertia weights

2017 8th International Conference on Computing, Communication and Networking Technologies (ICCCNT), 2017
Particle swarm optimization is widely used in past decades as optimization method for unimodal, multimodal, separable and non-separable optimization problems. A popular variant of PSO is PSO-W (Inertia Weight PSO). Attempts has made to modify the PSO with Selective Multiple Inertia Weights (SMIWPSO) to enhance the searching capability of PSO.
Indresh Kumar Gupta, Abha Choubey, Siddhartha Choubey   +2 more
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A New Fuzzy Inertia Weight Particle Swarm Optimization

2009 International Conference on Computational Intelligence and Natural Computing, 2009
This paper proposes a new Fuzzy tuned Inertia weight Particle Swarm Optimization (FIPSO) which remarkably outperforms the standard PSO, previous fuzzy as well as adaptive based PSO methods. Two benchmark functions with asymmetric initial range settings are used to validate the proposed algorithm and compare its performance with those of the other tuned
Peyman Yadmellat, S. Mohammad Amin Salehizadeh, Mohammad Bagher Menhaj   +2 more
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Exponential Inertia Weight for Particle Swarm Optimization

2012
The exponential inertia weight is proposed in this work aiming to improve the search quality of Particle Swarm Optimization (PSO) algorithm. This idea is based on the adaptive crossover rate used in Differential Evolution (DE) algorithm. The same formula is adopted and applied to inertia weight, w.
T. O. Ting, Yuhui Shi, Shi Cheng, Sanghyuk Lee   +3 more
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A novel PSO with piecewise-varied inertia weight

2010 2nd IEEE International Conference on Information and Financial Engineering, 2010
To choose the appropriate value of inertia weight can improve the performance of PSO by means of making a good balance between exploration and exploitation in search process. This paper presents a novel inertia weight variation method based on a piecewise function, in which there are two parts: one is nonlinear decreasing to enhance the explorative ...
Qin Quande, Li Li, Li Rongjun
openaire   +1 more source