In the recent restructured power system scenario and complex market strategy, operation at absolute minimum cost is no longer the only criterion for dispatching electric power. The economic load dispatch (ELD) problem which accounts for minimization of both generations cost and power loss is itself a multiple conflicting objective function problem. In this paper, a modified shuffled frog-leapin...

Cuckoo search (CS) is a novel biologically inspired algorithm and has been widely applied to many fields. Although some binary-coded CS variants are developed to solve 0-1 knapsack problems, the search accuracy and the convergence speed are still needed to further improve. According to the analysis of the shortcomings of the standard CS and the advantage of the global harmony search (GHS), a no...

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 ...

Microarray gene expression data play a vital in biological processes, gene regulation and disease mechanism. Biclustering in gene expression data is a subset of the genes indicating consistent patterns under the subset of the conditions. Finding a biclustering is an optimization problem. In recent years, swarm intelligence techniques are popular due to the fact that many real-world problems are...

Abstract Efficient and accurate porosity prediction is essential for the fine description of reservoirs, which an optimized BP neural network (BPNN) model proposed. Aiming at problem that BPNN sensitive to initialization converges local optimum easily, improved shuffled frog leaping algorithm (ISFLA) proposed based on roulette genetic coding. Firstly, a mechanism introduced improve selection pr...