An improved particle swarm optimization (IPSO) was proposed and the intelligent algorithms such as IPSO, genetic algorithm (GA), and simulated annealing algorithm (SA) were introduced to determine parameters of Van Genuchten (VG) model for soil water retention curve (SWRC) of four typical agricultural soil textures (clay, clay loam, silt loam and sand loam) in China. For comparison, the SWRC in...

Micro-grid is a kind of distributed low-voltage supply network by integrating various distributed powers, energy storage systems and controlled load. In micro-grid, distributed power can be divided into certain and stochastic power. The prediction on supply capacity of micro-grid focuses on electric energy production by stochastic power. The wind energy power is predicted in this paper by suppo...

This article analyzes and compares the integration of two different maximum power point tracking (MPPT) control methods, which are tested under partial shading fast ramp conditions. These MPPT methods designed by Improved Particle Swarm Optimization (IPSO) a combination technique between Neural Network Perturb Observe method (NN-P&O). implemented simulated for photovoltaic systems (PV), whe...

Making full use of abundant renewable solar energy through the development of photovoltaic (PV) technology is an effective means to solve the problems such as difficulty in electricity supply and energy shortages in remote rural areas. In order to improve the electricity generating efficiency of PV cells, it is necessary to track the maximum power point of PV array, which is difficult to make u...

With the development of sensor technology, network technology, embedded control technology and wireless communication technology, the application of wireless sensor networks (WSN) has become more and more widely. Wireless sensor networks have been named the most influential and important technology of the world in twenty-first Century. In wireless sensor networks, data fusion is an important re...

This study minimizes the periodic preventive maintenance cost for a series-parallel system using an improved particle swam optimization (IPSO). The optimal maintenance periods for all components in the system are determined efficiently. Though having advantages such as simple understanding and easy operation, a typical particle swam optimization (PSO) is easily trapped in local solutions when o...

in this paper, a chaotic particle swarm optimization with mutation-based classifier particle swarm optimization is proposed to classifypatterns of different classes in the feature space. the introduced mutation operators and chaotic sequences allows us to overcomethe problem of early convergence into a local minima associated with particle swarm optimization algorithms. that is, the mutationope...

In recent times, big data has become an essential concern with the rapid increase of digitalization. The problems that find solutions to finding and evaluating features are called optimization problems. this paper, sets containing EEG signals have been studied. goal is detect actual while eliminating additional brain activity patterns in collected data, resulting more accurate interpretation. s...

numerous problems encountered in real life cannot be actually formulated as a single objective problem; hence the requirement of multi-objective optimization (moo) had arisen several years ago. due to the complexities in such type of problems powerful heuristic techniques were needed, which has been strongly satisfied by swarm intelligence (si) techniques. particle swarm optimization (pso) has ...