In order to improve the estimation accuracy of state charge (SOC) electric vehicle power batteries, a dual Kalman filter method based on online identification model parameters is proposed estimate in lithium-ion batteries. Here, we build first-order equivalent circuit batteries and derive its extended (EKF). Considering that noise value EKF algorithm difficult select through experiments achieve...

Stock market volatility has a significant impact on many economic and financial activities in the world. Forecasting stock price movement plays an important role setting investment strategy or determining right timing for trading. However, movements are noisy, nonlinear, chaotic. It is difficult to forecast trends improving return investment. Here, we proposed novel improved particle swarm opti...

This paper presents an analysis of the relationship of particle velocity and convergence of the particle swarm optimization. Its premature convergence is due to the decrease of particle velocity in search space that leads to a total implosion and ultimately fitness stagnation of the swarm. An improved algorithm which introduces a velocity differential evolution (DE) strategy for the hierarchica...

The feature selection process constitutes a commonly encountered problem of global combinatorial optimization. This process reduces the number of features by removing irrelevant, noisy, and redundant data, thus resulting in acceptable classification accuracy. Feature selection is a preprocessing technique with great importance in the fields of data analysis and information retrieval processing,...

The feature selection process constitutes a commonly encountered problem of global combinatorial optimization. This process reduces the number of features by removing irrelevant, noisy, and redundant data, thus resulting in acceptable classification accuracy. Feature selection is a preprocessing technique with great importance in the fields of data analysis and information retrieval processing,...

the simultaneous optimization of multiple responses is an important problem in the design of industrial processes in order to achieve improved quality. in this paper, we present a new metaheuristic approach including simulated annealing and particle swarm optimization to optimize all responses simultaneously. for the purpose of illustration and comparison, the proposed approach is applied to tw...

Swarm Intelligence is the global intelligent behaviour emerged from the interaction of groups of simple agents. The existing swarm intelligence research mainly refers to swarm intelligence optimization, which with ant colony optimization and particle swarm optimization as a representative. And the relevant research work focuses on the performance improvements of the optimization algorithm, whic...

In this paper particle swarm optimization (PSO) is used for a design optimization of a linear permanent magnet synchronous motor (LPMSM) considering ultra low thrust force ripples, low magnet consumption, improved efficiency and thrust. The influence of PM material is discussed, too and the modular poles are proposed to achieve the best characteristic. PM dimensions and material, air gap and mo...

Research Scholar ,Dept. Of Electrical Engineering,S.I.E.T.,SHAUTS,U.P,INDIA Head of the Department ,Dept. Of Electrical Engineering, S.I.E.T.,SHAUTS,U.P,INDIA ---------------------------------------------------------------------------***----------------------------------------------------------------------------ABSTRACT: In this paper we are simplify the model of an islanded micro-grid systems ...

the dogleg severity is one of the most important parameters in directional drilling. improvement of these indicators actually means choosing the best conditions for the directional drilling in order to reach the target point. selection of high levels of the dogleg severity actually means minimizing well trajectory, but on the other hand, increases fatigue in drill string, increases torque and d...