نتایج جستجو برای: the modified particle swarm optimization mpso

تعداد نتایج: 16191741  

2011
D. Y. Sha Hsing-Hung Lin

Multi-objective open-shop scheduling is definitely significant in practical. However, the research focused on multi-objective open-shop scheduling was relatively scarce. This article proposed a particle swarm optimization to address open-shop scheduling problems with multiple objectives. Originally, particle swarm optimization was invented to treat continuous optimization problems. In this pape...

Journal: :CoRR 2015
Alexandros E. Paschos Vasileios M. Kapinas Leontios J. Hadjileontiadis George K. Karagiannidis

A novel optimization algorithm, called accelerated particle swarm optimization (APSO), is proposed to be used for dynamic spectrum sensing in cognitive radio networks. While modified swarm-based optimization algorithms focus on slight variations of the standard mathematical formulas, in APSO, the acceleration variable of the particles is also considered in the search space. We show that the pro...

Journal: :international journal of civil engineering 0
m.h. afshar r. rajabpour

this paper presents a relatively new management model for the optimal design and operation of irrigation water pumping systems. the model makes use of the newly introduced particle swarm optimization algorithm. a two step optimization model is developed and solved with the particle swarm optimization method. the model first carries out an exhaustive enumeration search for all feasible sets of p...

2013
Michal Pluhacek Roman Senkerik Ivan Zelinka Donald Davendra

A new promising strategy for the PSO (Particle swarm optimization) algorithm is proposed and described in this paper. This new strategy presents alternative way of assigning new velocity to each individual in particle swarm (population). This new multiple choice particle swarm optimization (MC-PSO) algorithm is tested on two different shifted test functions to show the performance on problems t...

Journal: :Mathematical Problems in Engineering 2022

The height of the water flowing fractured zone (HWFFZ) is key parameter for safe coal mining under bodies. In order to improve accuracy prediction model HWFFZ, grey relational analysis (GRA) used quantitatively analyze influencing factors main HWFFZ condition comprehensive mechanized and top caving are selected scientifically, these five that include depth, thickness, inclined length working fa...

Journal: :journal of computer and robotics 0
mojtaba gholamian faculty of computer and information technology engineering, qazvin branch, islamic azad university, qazvin, iran mohammad reza meybodi department of computer engineering and information technology, amirkabir university of technology, tehran, iran

so far various methods for optimization presented and one of most popular of them are optimization algorithms based on swarm intelligence and also one of most successful of them is particle swarm optimization (pso). prior some efforts by applying fuzzy logic for improving defects of pso such as trapping in local optimums and early convergence has been done. moreover to overcome the problem of i...

2013
Jie He Hui Guo

In optimizing the particle swarm optimization (PSO) that inevitable existence problem of prematurity and the local convergence, this paper base on this aspects is put forward a kind of modified particle swarm optimization algorithm, take the gradient descent method (BP algorithm) as a particle swarm operator embedded in particle swarm algorithm, and at the same time use to attenuation wall (Dam...

Journal: :International Journal of Computer Applications 2017

2013
KJV SATISH BABU HARSHAVARDHAN REDDY M PADMA LALITHA

Today’s changing electric power systems create a growing need for flexibility, reliability, fast response and accuracy in the fields of electric power generation, transmission, distribution and consumption. Power system networks are complex systems that are nonlinear, disturbances and faults. It can be accomplished by improving the voltage profile, enhancement of voltage stability and by reduci...

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