In the paper a modified particle swarm optimization (MPSO) is proposed where concepts from firefly algorithm (FA) are borrowed to enhance the performance of particle swarm optimization (PSO). The modifications focus on the velocity vectors of the PSO, which fully use beneficial information of the position of particles and increase randomization item in the PSO. Finally, the performance of the p...

This paper presents a novel modified particle swarm optimization algorithm (MPSO) for both offline and online parametric identification of dynamic models. The MPSO is applied for identifying a suspension system introduced by a quarter-car model. A novel mutation mechanism is employed in MPSO to enhance global search ability and increase convergence speed of basic PSO (BPSO) algorithm. MPSO opti...

Automation of power system nowadays is one of the great spreading fields in electrical engineering. Artificial Intelligence Technique helps in developing and modifying the automated power system. The particle swarm optimization (PSO) technique is one of the recent artificial intelligent techniques. In this thesis a modified particle swarm optimization (MPSO) is utilized in Unit Commitment Probl...

The structure optimization of main beam is a nonlinear constrained optimization problem, which is important for bridge crane to save manufacturing cost on quality assurance. The modified particle swarm optimization (MPSO) with feasibility-based rules [1], which was advanced to solve mixed-variable optimization problems, is proposed to optimize the structure of main beam in order to find the opt...

This paper proposes a Modified Particle Swarm Optimization with Time Varying Acceleration Coefficients (MPSO-TVAC) for solving economic load dispatch (ELD) problem. Due to prohibited operating zones (POZ) and ramp rate limits of the practical generators, the ELD problems become nonlinear and nonconvex optimization problem. Furthermore, the ELD problem may be more complicated if transmission los...

Electrical impedance tomography (EIT) reconstructs the internal impedance distribution of the body from electrical measurements on body surface. The algorithm research is one of the main problems of the EIT. This paper presents the MPSO-MNR Algorithm, which is formed by combining the Modified Particle Swarm Optimization (MPSO) with Modified Newton-Raphson algorithm (MNR), gives the reconstructi...

The main purpose of data mining is to extract hidden predictive knowledge of useful information and patterns of data from large databases for utilizing it in decision support. Medical field has large amount of various heterogeneous databases, in which the extraction of hidden useful knowledge for the classification of data is difficult one. In order to cluster and classify the whole databases o...

A novel technique for the optimal tuning of power system stabilizer (PSS) was proposed, by integrating the modified particle swarm optimization (MPSO) with the chaos (MPSOC). Firstly, a modification in the particle swarm optimization (PSO) was made by introducing passive congregation (PC). It helps each swarm member in receiving a multitude of information from other members and thus decreases t...

This paper present a new method to determine the optimal tuning of the PID controller parameter of an AVR system using Modified particle swarm optimization (MPSO) algorithm. the AVR is not robust to variations of the power system parameters therefore, it is necessary to use PID controller To increase the stability and performance of the AVR system. Fast tuning of optimum PID controller paramete...

This paper builds the power transformer diagnosis model based on the improved particle swarm optimization— support vector machine (MPSO-SVM). Speed update and particle self-adaptation self-variation are introduced to optimize the standard particle swarm algorithm, thus overcoming the defect of the standard particle swarm optimization algorithm and increasing the power transformer fault diagnosi...