The present paper proposes a fault diagnosis methodology of three phase inverter circuit base on radial basis function (RBF) artificial neural network trained by particle swarm optimization (PSO) algorithm. Using the appropriate stimulus signal, fault features are extracted from efficient points in frequency response of the circuit directly and then a fault dictionary is created by collecting s...

optimization techniques can be efficiently utilized to achieve an optimal shape for arch dams. this optimal design can consider the conditions of the economy and safety simultaneously. the main aim is to present an applicable and practical model and suggest an algorithm for optimization of concrete arch dams to enhance their seismic performance. to achieve this purpose, a preliminary optimizati...

Most of neural network training algorithms make use of gradient-based search and because of their disadvantages, researchers always interested in using alternative methods. In this paper to train feedforward, neural network for prediction problems a new Hybrid Improved Opposition-based Particle swarm optimization and Genetic Algorithm (HIOPGA) is proposed. The opposition-based PSO is utilized t...

Loan default evaluation and discrimination is a complicated issue because of its nonlinearity and uncertainty. Least square support vector machine (LS-SVM) has been successfully employed to solve regression and time series problem. This paper proposes a novel PSO-LS-SVM model based on the improved PSO algorithm to optimize parameters of LS-SVM, which is a new improved form by synthesizing the e...

neural network is one of the most widely used algorithms in the field of machine learning, on the other hand, neural network training is a complicated and important process. supervised learning needs to be organized to reach the goal as soon as possible. a supervised learning algorithm analyzes the training data and produces an inferred function, which can be used for mapping new examples.  hen...

Artificial Neural Network (ANN) design has long been a complex problem because its performance depends heavily on the network topology and algorithm to train the set of synaptic weights. Particle Swarm Optimization (PSO) has been the favored optimization algorithm to complement ANN, but a thorough literature study has shown that there are gaps with current approaches which integrate PSO with AN...

this paper presents a hybrid approach to developing a short-term traffic flow prediction model. in thisapproach a primary model is synthesized based on neural networks and then the model structure is optimized throughgenetic algorithm. the proposed approach is applied to a rural highway, ghazvin-rasht road in iran. the obtainedresults are acceptable and indicate that the proposed approach can i...

Back propagation algorithm (BPA) have the complexity, local minima problem so we are using Particle Swarm optimization (PSO) algorithms to reduce and optimize BPA. In this paper, two variants of Particle Swarm Optimization (PSO) PSO_Hill and PSO_A* is used as optimization algorithm. PSO_Hill and PSO_A* algorithms are analyzed and evaluated on the basis of their advantages, applied to feed forwa...