In this paper, we propose Hybrid Particle Swarm Optimization (HPSO) with genetic algorithm(GA) mutation to optimize the SVM forecasting model. In the process of doing so, we first use HPSO with genetic algorithm to make pretreatment of the data. PSO with GA model is a method for finding a solution of stochastic global optimizer based on swarm intelligence. Using the interaction of particles, PS...

Energy management carried in a power system by configuration process is difficult activity. So, reconfiguration has been introduced to solve this problem. Numerous optimization topologies have utilized problem so far. However, they exhibit some drawbacks such as convergence, etc. Hence overcome issue, work formulated new hybrid topology Genetic Algorithm Enabled Particle Swarm Optimization (PSO...

This paper describes an evolutionary strategy called PSOGA-NN, which uses Neural Network (NN) for selfadaptive control of hybrid Particle Swarm Optimization and Adaptive Plan system with Genetic Algorithm (PSO-APGA) to solve large scale problems and constrained real-parameter optimization. This approach combines the search ability of all optimization techniques (PSO, GA) for stability of conver...

Meta-heuristics have already received considerable attention in various engineering optimization fields. As one of the most rewarding tasks, eigenvalue optimization of truss structures is concerned in this study. In the proposed problem formulation the fundamental eigenvalue is to be maximized for a constant structural weight. The optimum is searched using Particle Swarm Optimization, PSO and i...

A number of algorithms based on the evolutionary processing have been proposed forcommunication networks backbone such as Genetic Algorithm (GA). However, there has beenlittle work on the SWARM optimization algorithms such as Particle Swarm Optimization(PSO) for backbone topology design. In this paper, the performance of PSO on GA isdiscussed and a new algorithm as PSOGA is proposed for the net...

The main purpose of using the hybrid evolutionary algorithm is to reach optimal values and achieve goals that traditional methods cannot because there are different computations, each them has advantages capabilities. Therefore, researchers integrate more than one into a form increase ability these algorithms perform computation when working alone. In this paper, we propose new for genetic (GA)...

The purpose of this research is to develop an efficient single-phase grid-connected PV system using a better performing asymmetrical multilevel inverter (AMI). Circuit component reduction, harmonic and grid integration are critical criteria for efficiency. proposed inverter’s optimized topology requires seven unidirectional switches, three symmetric dc sources, diodes produce asymmetric fifteen...

Accurate and timely weather forecasting is a major challenge for the scientific community in hydrological research such as river training works and design of flood warning systems. Neural Network (NN) is a popular regression method in rainfall predictive modeling. This paper investigates the effectiveness of the hybrid Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) evolved neural ...