Particle swarm optimization algorithm in solving complex functions, such as slow convergence, accuracy is not high, easily falling into local optimum problem. Based on the chaos optimization is introduced into particle swarm optimization algorithm, given the chaotic particle swarm optimization algorithm. In order to improve the image quality of CMOS image sensor, the image of the main noise sou...

Abstract—In this paper, an intelligent backstepping controller, tuned using a chaotic particle swarm optimization (CPSO), is proposed to control of chaos in Genesio-Tesi chaotic system. Thebackstepping method consists of parameters with positive values. The parameters are usually chosen optional by trial and error method. The improper selection of the parameters leads to inappropriate responses...

This paper deals with the design of optimal backstepping controller, by using the chaotic particle swarm optimization (CPSO) algorithm to control of chaos in Lur’e like chaotic system. The backstepping method consists of parameters which could have positive values. The parameters are usually chosen optional by trial and error method. The controlled system provides different behaviors for differ...

The classification accuracy of the least squares support vector machine (LSSVM) models strongly depends on proper setting of its parameters. An optimal selection approach of LSSVM parameters is put forward based on multi-swarm cooperative chaos particle swarm optimization (MCCPSO) algorithm. Chaos particle swarm optimization (CPSO) can improve the ability of local search optimization with good ...

In this paper, the Unified Power Flow Controller (UPFC) is enhanced with a Chaotic Particle Swarm Optimization (CPSO) Damping Controller in order to mitigate the Low Frequency Oscillations (LFO) in a Single Machine Infinite Bus (SMIB) power system. The designed damping controller is an optimized lead-lag controller, which extracts the speed deviation of the generator rotor and generates the out...

The effectiveness of wireless sensor networks (WSNs) depends on the coverage and target detection probability provided by dynamic deployment, which is usually supported by the virtual force (VF) algorithm. However, in the VF algorithm, the virtual force exerted by stationary sensor nodes will hinder the movement of mobile sensor nodes. Particle swarm optimization (PSO) is introduced as another ...

Wind speed forecasting is difficult not only because of the influence of atmospheric dynamics but also for the impossibility of providing an accurate prediction with traditional statistical forecasting models that work by discovering an inner relationship within historical records. This paper develops a self-adaptive (SA) auto-regressive integrated moving average with exogenous variables (ARIMA...

This paper presents an approach to the design of optimal control strategy for plug-in hybrid electric vehicles (PHEVs) incorporating Internet Vehicles (IoVs). The is designed and implemented by employing a mobile edge computing (MEC) based framework IoVs. thresholds in can be instantaneously optimized chaotic particle swarm optimization with sequential quadratic programming (CPSO-SQP) units (ME...

To resolve the problems that cloud particle swarm optimization (CPSO) was easily trapped in local minimum and possessed slow convergence speed and early-maturing during distribution grid reactive power optimization, CPSO algorithm was improved based on cloud digital features in this paper. The method combined Local search with global search together based on solution space transform, where the ...

The losses in electrical power systems are a great problem. Multiple methods have been utilized to decrease transmission lines. proper adjusting of reactive resources is one way minimize the any system. Reactive Power Optimization (RPO) problem nonlinear and complex optimization contains equality inequality constraints. RPO highly essential operation control systems. Therefore, study concentrat...