نتایج جستجو برای: objective particle swarm optimization
تعداد نتایج: 998346 فیلتر نتایج به سال:
Gait identification task becomes difficult due to the change of appearance by different cofactors (e.g., shoe, surface, carrying, view, and clothing). Some parts of gait are affected by cofactors and other parts remains unaffected. Most of the gait identification systems consider only most effective parts thereby omitting less effective parts. However some significant features for gait identifi...
Many real world optimization problems are dynamic, meaning that their optimal solutions are time-varying. In recent years, an effective approach to address these problems has been the multi-swarm PSO (mPSO). Despite this, we believe that there is still room for improvement and, in this contribution we propose two simple strategies to increase the effectiveness of mPSO. The first one faces the d...
A mobile ad-hoc network (MANET), a set of wirelessly connected sensor nodes, is a dynamic system that executes hop-by-hop routing independently with no external help of any infrastructure. Proper selection of cluster heads can increase the life time of the Ad-hoc network by decreasing the energy consumption. Although different methods have been successfully proposed by researchers to tackle...
This study compares a number of selection regimes for the choosing of global best (gbest) and personal best (pbest) for swarm members in multi-objective particle swarm optimisation (MOPSO). Two distinct gbest selection techniques are shown to exist in the literature, those that do not restrict the selection of archive members and those with ‘distance’ based gbest selection techniques. Theoretic...
A newmultiobjective particle swarm optimization (MOPSO) technique for environmental/economic dispatch (EED) problem is proposed in this paper. The proposed MOPSO technique evolves a multiobjective version of PSO by proposing redefinition of global best and local best individuals in multiobjective optimization domain. The proposedMOPSO technique has been implemented to solve the EED problemwith ...
Abstract: One of the equipment that can help improve distribution system status today and reduce the cost of fault time is remote control switches (RCS). Finding the optimal location and number of these switches in the distribution system can be modeled with various objective functions as a nonlinear optimization problem to improve system reliability and cost. In this article, a particle swarm ...
differential steering of in-wheel electric vehicle provides the functions of both active steering and power assisted steering with the coupling control of force and displacement transfer characteristic of system. a collaborative optimization model of the differential power-assisted steering system of in-wheel electric vehicle is built, with steering economy as the main system optimization goal,...
مسئله ی یافتن کلیک بیشینه گراف maximum clique problem (mcp)، از جمله مسائل np-complete است که به یافتن بزرگترین زیرگراف کامل در یک گراف ساده اشاره دارد و در موارد متنوعی از جمله نظریه کدگذاری، هندسه و شبکه های اجتماعی کاربرد دارد. در این پژوهش الگوریتمی ترکیبی برای حل مسئله ی کلیک بیشینه گراف پیشنهاد شده است. این الگوریتم ترکیبی از یک روش حریصانه ابتکاری و الگوریتم های مبتنی بر هوش جمعی بهینه س...
With the rapid development of swarm intelligence research field, a large number of algorithms in swarm intelligence are proposed one after another. The strong points and the drawbacks of a specific swarm intelligence algorithm becomes clear to be seen when the number of its application increases. To overcome the handicaps, some hybrid methods are invented. In this review, three hybrid swarm int...
The fast convergence of particle swarm algorithms can become a downside in multi-objective optimization problems when there are many local optimal fronts. In such a situation a multi-objective particle swarm algorithm may get stuck to a local Pareto optimal front. In this paper we propose a new approach in selecting leaders for the particles to follow, which in-turn will guide the algorithm tow...
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