This paper presents a new approach that minimizes copper & iron losses and optimizes the efficiency of a variable speed Induction motor drive. This method is based on a simple induction motor field oriented control model includes iron losses uses only conventional IM parameters. In literature, Fuzzy logic and Genetic Algorithms have been used for efficiency optimization of induction motor drive...

This paper presents a new approach that minimizes copper & iron losses and optimizes the efficiency of a variable speed Induction motor drive. This method is based on a simple induction motor field oriented control model includes iron losses uses only conventional IM parameters. In literature, Fuzzy logic and Genetic Algorithms have been used for efficiency optimization of induction motor drive...

It has proposed a kind of hybrid method based on intuitionistic fuzzy set theory and particle swarm optimization (PSO) algorithm-based neural network (NN). We apply it to the integrative damage effect assessment of battlefield target. Firstly, we improve PSO algorithm, propose the adaptive inertia factor and excellence selection mechanism, introduce inter-partition particle swarm initialization...

This work aims at proposing a robust strategy to determine the optimal operating parameters based on fuzzy modeling for enhancing productivity of methane using Pelvetia canaliculata. The applied is combination logic (FL) and particle swarm optimizer (PSO). First, FL used build model that describes production experimental datasets. Second, PSO algorithm obtain best-operating conditions process. ...

Abstract: In this paper, the gain in LD-CELP speech coding algorithm is predicted using three neural models, that are equipped by genetic and particle swarm optimization (PSO) algorithms to optimize the structure and parameters of neural networks. Elman, multi-layer perceptron (MLP) and fuzzy ARTMAP are the candidate neural models. The optimized number of nodes in the first and second hidden la...

This paper presents a novel improved fuzzy particle swarm optimization (IFPSO) algorithm to the intelligent identification and control of a dynamic system. The proposed algorithm estimates optimally the parameters of system and controller by minimizing the mean of squared errors. The particle swarm optimization is enhanced intelligently by using a fuzzy inertia weight to rationally balance the ...

In this paper, the gain in LD-CELP speech coding algorithm is predicted using three neural models, that are equipped by genetic and particle swarm optimization (PSO) algorithms to optimize the structure and parameters of neural networks. Elman, multi-layer perceptron (MLP) and fuzzy ARTMAP are the candidate neural models. The optimized number of nodes in the first and second hidden layers of El...

This article presents a new technique to detect a premature atrial contraction (PAC). The technique employs a hybrid of particle swarm optimization (PSO) and fuzzy inference system (FIS), and is called PSO-FIS. In the detection electrocardiographic features are used for the inputs of PSO-FIS. In PSO-FIS, a PSO is used to find the optimal parameters of the FIS. A Gaussian function is employed fo...

In order to accurately, fast and efficiently forecast the short-term load of power system, an improved particle swarm optimization algorithm is proposed to optimize the parameters of fuzzy radial basis function fuzzy neural network(FRBFNN) model in order to train the FRBFNN model for obtaining the optimized FRBFNN(IWPSRFN) method. In the proposed IWPSRFN method, the linear decreasing weight met...