Abstract The differential evolution (DE) algorithm is an efficient random search based on swarm intelligence for solving optimization problems. It has the advantages of easy implementation, fast convergence, strong ability and good robustness. However, performance DE very sensitive to design different operators setting control parameters. To solve these key problems, this paper proposes improve...

Feature selection in cancer classification is a central area of research in the field of bioinformatics and used to select the informative genes from thousands of genes of the microarray. The genes are ranked based on T-statistics, signal-to-noise ratio (SNR), and F-test values. The swarm intelligence (SI) technique finds the informative genes from the top-m ranked genes. These selected genes a...

In order to minimize power losses caused by high current and improve the voltage profile in the network distribution, the introduction of dispersed generations also called productions decentralized in distribution network (DG) plays an important role. The installation of DGs directly affects the power requested or purchased. The sizing and placement of DGs in the system must be optimal because ...

The frequency modulation sound parameter identification is a complex multimodal optimization problem. This problem is modeled in the form of a cost function that is the sum-squared error between the samples of estimated wave and the samples of real wave. In this research, the authors propose a shuffled particle swarm optimization algorithm to solve this problem. In the shuffled particle swam op...

This paper proposes Hybrid SFL-Bees Algorithm that combines strengths of Shuffled Frog Leaping Algorithm (SFLA) and Bees Algorithms (BA). While SFLA can find optimal solutions quickly because of directive searching and exchange of information, BA has higher random that make it easily escape local optima to find global solutions. Thus Hybrid SFL-Bees Algorithm is able to find optimal solutions q...

Reducing energy consumption is becoming very important in order to keep battery life and lower overall operational costs for heterogeneous real-time multiprocessor systems. In this paper, we first formulate this as a combinatorial optimization problem. Then, a successful meta-heuristic, called Shuffled Frog Leaping Algorithm (SFLA) is proposed to reduce the energy consumption. Precocity remissi...

This paper shows the results obtained in the analysis of the impact of Distributed Generation (DG) on distribution losses and presents a new algorithm to the optimal allocation of distributed generation resources in distribution networks. The optimization is based on a Shuffled Frog Leaping Algorithm (SFLA) aiming to optimal DG allocation in distribution network. Shuffled frogleaping algorithm ...

Restructuring the recent developments in the power system and problems arising from construction as well as the maintenance of large power plants lead to increase in using the Distributed Generation (DG) resources. DG units due to its specifications, technology and location network connectivity can improve system and load point reliability indices. In this paper, the allocation and sizing of di...

Among the existing GDP forecasting methods, time series and regression model are two most commonly used methods. However, traditional macroeconomic models unable to accurately achieve optimal forecasts of highly complex nonlinear dynamic systems due influence multiple confounding factors. In order solve above problems, a economic based on an improved RBF neural network is proposed. First, main ...