Detection of squirrel cage induction motor (SCIM) broken bars has long been an important but difficult job in the detection area of motor faults. Early detection of this abnormality in the motor would help to avoid costly breakdowns. A new detection method based on particle swarm optimization (PSO) is presented in this paper. Stator current in an induction motor will be measured and characteris...

The short-term load forecasting is an important method for security dispatching and economical operation in electric power system, and its prediction accuracy directly affects the operating reliability of the electric system. So the global optimization ability of particle swarm optimization (PSO) algorithm and classification prediction ability of support vector machine (SVM) are combined in ord...

Feature selection and classifier hyper-parameter optimization are important stages of any computer-aided diagnosis (CADx) system for mammography. The optimal selection for shape features, kernel parameter, and classifier regularization constant is crucial to achieve a good generalization and performance of least-squares support vector machines (LSSVMs). This paper presents a morphology-based CA...

In recent years, particle swarm optimization (PSO) proposed by Kennedy et al. has been widely used as a general approximate solution method for optimization problems. The authors proposed a revised PSO (rPSO) method incorporating the homomorphous mapping and the multiple stretching technique in order to cope with shortcomings of PSO and showed its efficiency for nonlinear programming problems. ...

Most existing task scheduling algorithms in cloud storage fail to aware users ' QoS preference. In addition, these algorithms result in low user satisfaction rate for they do not consider the characteristics of cloud storage. In order to address these problems, the "optimal order comparison method” is used to aware users ' QoS preference, and also helps experts use their professional knowledge ...

Optimal placement and sizing of DG in distribution network is an optimization problem with continuous and discrete variables. Many researchers have used evolutionary methods for finding the optimal DG placement and sizing. This paper proposes a hybrid algorithm PSO&HBMO for optimal placement and sizing of distributed generation (DG) in radial distribution system to minimize the total power loss...

This Paper presents a comparative study of Genetic Algorithm method (GA) and Particle swarm optimization (PSO) method to determine the optimal proportional-integral (PI) and proportional-integral-derivative (PID) controller parameters, for speed control of a Field Oriented Control (FOC) induction motor. The FOC induction motor has been modeled in MATLAB (SIMULINK); the GA and PSO algorithm has ...

In this paper, optimal generation expansion planning (GEP) is investigated considering purchase prices, profits of independent power producers (IPPs) and reliability criteria using a new method based on hybrid coded Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). In this approach, optimal purchase price of each IPP is obtained by HCGA and reliability criteria are calculated by PSO...

In this study, video super-resolution using particle swarm optimization (PSO) is proposed to super-resolve low-resolution (LR) frames. The proposed super-resolution method consists of three main modules, i.e., supersampling, spatio-temporal classification, and frame fusion using PSO. In the proposed method, the LR frames are super-resolved to high-resolution frames through the fusion of four fu...

MAV (Micro Aerial Vehicle) is nonlinear plant, it is difficult to obtain stable control for MAV attitude due to uncertainties. The purpose of this paper is to propose one robust 、 stable control strategy for MAV to accommodate system uncertainties, variations, and external disturbances. In this paper, an interval type II fuzzy sliding-mode controller combined with PSO algorithm (ITIIFSMC-PSO) i...