نتایج جستجو برای: genetic algorithm ga and particle swarm optimization pso algorithm
تعداد نتایج: 17050101 فیلتر نتایج به سال:
Protection systems have vital role in network reliability in short circuit mode and proper operating for relays. Current transformer often in transient and saturation under short circuit mode causes mal-operation of relays which will have undesirable effects. Therefore, proper and quick identification of Current transformer saturation is so important. In this paper, an Artificial Neural Network...
Support vector machine (SVM) is a popular pattern classification method with many application areas. SVM shows its outstanding performance in high-dimensional data classification. In the process of classification, SVM kernel parameter setting during the SVM training procedure, along with the feature selection significantly influences the classification accuracy. This paper proposes two novel in...
Finding appropriate features is one of the key problems in the increasing applications of rough set theory, which is also one of the bottlenecks of the rough set methodology. Particle Swarm Optimization (PSO) is particularly attractive for this challenging problem. In this paper, we attempt to solve the problem using a particle swarm optimization approach. The proposed approach discover the bes...
The genetic algorithm (GA) is an evolutionary optimization algorithm operating based upon reproduction, crossover and mutation. On the other hand, particle swarm optimization (PSO) is a swarm intelligence algorithm functioning by means of inertia weight, learning factors and the mutation probability based upon fuzzy rules. In this paper, particle swarm optimization in association with genetic a...
The genetic algorithm (GA) is an evolutionary optimization algorithm operating based upon reproduction, crossover and mutation. On the other hand, particle swarm optimization (PSO) is a swarm intelligence algorithm functioning by means of inertia weight, learning factors and the mutation probability based upon fuzzy rules. In this paper, particle swarm optimization in association with genetic a...
In this paper a new effective optimization algorithm called hybrid particle swarm optimizer with breeding and subpopulation is presented. This algorithm is essentially, as PSO and GA, a population-based heuristic search technique, now in use for the optimization of electromagnetic structures, modeled on the concepts of natural selection and evolution (GA) but also based on cultural and social r...
voltage stability issues are growing challenges in many modern power systems. this paper proposes optimizing the size and location of static var compensator (svc) devices using a fuzzy weighted seeker optimization algorithm (fwsoa), as an effective solution to overcome such issues. although the primary purpose of svc is bus voltage regulation, it can also be useful for voltage stability enhance...
Optimization is necessary for the control of any process to achieve better product quality, high productivity with low cost. The beltline moulding process is difficult task due to its low defects, making the material sensitive to reject. The efficient beltline moulding process involves the optimal selection of operating parameters to maximize the number of production while maintaining the requi...
The Vehicle Routing Problem can be expressed as the problem of designing optimal collection or delivery routes from one or multiple depots to a number of terrestrially scattered customers or cities, subject to side constraints such as time, capacity, mileage etc. The VRP plays a key role in the fields of logistics and transportation. There exist a number of variants of VRPs. Mostly VRPs with fi...
In this paper, optimal thresholds for multi-level thresholding in an image are obtained by maximizing the Tsallis entropy using cuckoo search algorithm. The method is considered as a constrained optimization problem. The solution is obtained through the convergence of a meta-heuristic search algorithm. The proposed algorithm is tested on standard set of images. The results are then compared wit...
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