Congestion management is one of the major tasks performed by system operators (SOs) to ensure the operation of transmission system within operating limits. To permit smooth and quality flow of power the problem of congestion has to be solved. The congestion in the transmission line will be removed by generation rescheduling with the cost involved in the rescheduling process should be minimized....

In order to design and optimize high-linearity power amplifier (PA), which with nonlinear and memory effect, it is very important to build power amplifier behavior modeling accurately. This paper proposes a power amplifier behavior modeling based on RBF neural network with improved chaos particle swarm optimization algorithm. To make the particles evenly distribute in the problem search space, ...

(Background) To solve the cluster analysis better, we propose a new method based on chaotic particle swarm optimization (CPSO) algorithm.
 (Methods) In order to enhance performance in clustering, novel CPSO. We first evaluate clustering of this model using Variance Ratio Criterion (VRC) as evaluation metric. The effectiveness CPSO algorithm is compared with that traditional Particle Swarm ...

Clustering is a popular data analysis and data mining technique. In this paper, a novel chaotic particle swarm fuzzy clustering (CPSFC) algorithm based on chaotic particle swarm (CPSO) and gradient method is proposed. Fuzzy clustering model optimization is challenging, in order to solve this problem, adaptive inertia weight factor (AIWF) and iterative chaotic map with infinite collapses (ICMIC)...

Vertical partition is an important technique in database design used to enhance performance in database systems. Vertical fragmentation is a combinatorial optimization problem that is NP-hard in most cases. We propose an application and an adaptation of an improved combinatorial particle swarm optimization (ICPSO) algorithm for the vertical fragmentation problem. The original CPSO algorithm [3]...

Many real-world problems are dynamic, requiring an optimization algorithm which is able to continuously track a changing optimum over time. In this paper, we present new variants of Particle Swarm Optimization (PSO) specifically designed to work well in dynamic environments. The main idea is to extend the single population PSO and Charged Particle Swarm Optimization (CPSO) methods by constructi...

To deal with pattern synthesis of antenna arrays, a chaotic particle swarm optimization (CPSO) is presented to avoid the premature convergence. By fusing with the ergodic and stochastic chaos, the novel algorithm explores the global optimum with the comprehensive learning strategy. The chaotic searching region can be adjusted adaptively. To evaluate the performance of CPSO, several representati...

As an important part of smart grid, EVs have many advantages in energy saving and low pollution and become a research hotspot. Based on the wireless power transfer technology, dynamic power supply technology develops rapidly and can effectively reduce the battery capacity of EVs. This paper the issue on the optimal design of sectional dynamic power supply track has been investigates the optimal...

In this paper, five previous Particle Swarm Optimization (PSO) algorithms for multimodal function optimization are reviewed. A new and a successful PSO based algorithm, named as CPSO is proposed. CPSO enhances the exploration and exploitation capabilities of PSO by performing search using a random walk and a hill climbing components. Furthermore, one of the previous PSO approaches is improved i...