نتایج جستجو برای: gravitational search algorithm gsa
تعداد نتایج: 1019509 فیلتر نتایج به سال:
This paper presents a methodology using Gravitational Search Algorithm for optimal placement of Phasor Measurement Units (PMUs) in order to achieve complete observability of the power system. The objective of proposed algorithm is to minimize the total number of PMUs at the power system buses, which in turn minimize installation cost of the PMUs. In this algorithm, the searcher agents are colle...
Image segmentation is useful in many applications. It can identify the regions of interest in a scene or annotate the data. It categorizes the existing segmentation algorithm into region-based segmentation, data clustering, and edge-base segmentation. Region-based segmentation includes the seeded and unseeded region growing algorithms, the JSEG, and the fast scanning algorithm. Due to the prese...
Utilizing QFD in the process of manufacturing and service performing is confronted with an optimization problem called QFD decision-making problem (QFDDMP). Facing many customer constraints and requirements, and huge number of customers in the target market have made QFDDMP a complex planning problem. Achieving optimal solution by which the products satisfy customers with lowest costing budget ...
Determining the optimum number of nodes, number of hidden layers, and synaptic connection weights in an artificial neural network (ANN) plays an important role in the performance of this soft computing model. Several methods have been proposed for weights update (training) and structure selection of the ANNs. For example, the error back-propagation (EBP) is a traditional method for weights...
The Gravitational Search Algorithm (GSA) is a novel heuristic optimization method based on the law of gravity and mass interactions. It has been proven that this algorithm has good ability to search for the global optimum, but it suffers from slow searching speed in the last iterations. This work proposes a hybrid of Particle Swarm Optimization (PSO) and GSA to resolve the aforementioned proble...
For predicting the key technology indicators (concentrate grade and tailings recovery rate) of flotation process, a feed-forward neural network (FNN) based soft-sensor model optimized by the hybrid algorithm combining particle swarm optimization (PSO) algorithm and gravitational search algorithm (GSA) is proposed. Although GSA has better optimization capability, it has slow convergence velocity...
GSA; Real power loss; Reactive power planning; FACTS; Optimization Abstract In this paper, Gravitational Search Algorithm (GSA) is used as optimization method in reactive power planning using FACTS (Flexible AC transmission system) devices. The planning problem is formulated as a single objective optimization problem where the real power loss and bus voltage deviations are minimized under diffe...
Abstract: In this paper, a generalized Lagrangian-based algorithm (TRALM) and gravitational search algorithm (GSA) are used to solve the Optimal Load Distribution Problem (OPF) in the presence of FACTS equipment. Four TCSC, TCPST UPFC and SVC equipment’s have been tested. Modeling of FACTS equipment is based on power injection method. To optimally manage production, losses and voltage profiles,...
In recent times, the demand for real-time multimedia applications is rapidly increased due to the increasing mobile users. Wireless Sensor Network (WSN) often suffers because of the overhead produced during message passing, constant energy and node cost. To provide solution to these issues, in this study, we propose Fuzzy and Gravitational Search Based Routing Protocol for Lifetime Enhancement ...
Gravitational search algorithm (GSA) has been recently presented as a new heuristic search algorithm with good results in real-valued and binary encoded optimization problems which is categorized in swarm intelligence optimization techniques. The aim of this article is to show that GSA is able to find multiple solutions in multimodal problems. Therefore, in this study, a new technique, namely N...
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