In this paper, a new hybrid methodology is introduced to design a cost-sensitive fuzzy rule-based classification system. A novel cost metric is proposed based on the combination of three different concepts: Entropy, Gini index and DKM criterion. In order to calculate the effective cost of patterns, a hybrid of fuzzy c-means clustering and particle swarm optimization algorithm is utilized. This ...

In this work, we will compare two approximation method based on hybrid Legendre and Block-Pulse functions and a computational method for solving nonlinear FredholmVolterra integral equations of the second kind which is based on replacement of the unknown function by truncated series of well known Block-Pulse functions (BPfs) expansion.

The aim of the present paper is to associate a new symmetric boundary integral method to well known symmetric domain methods with the purpose of improving solutions of multi-eld problems with coupled boundary and domain methods. From a single-eld variational principle for a 3D linear, elastodynamic state a three-eld hybrid principle is developed by Hamiltons principle and decoupling displacemen...

In this paper, we present a hybrid particle swarm optimization and support vector regression approach to predict exchange rate. This hybrid method examines the validity to optimize the parameters of penalty term and kernel function. For the experiments, the data of exchange rates (USD/CNY, EUR/CNY and CNY/JPY) are examined and optimized to be used for time series predictions with hybrid particl...

A local hybrid radial–polynomial approximation scheme is introduced here to modify the scattered data fitting method presented in [6], generating C1 or C2 approximating spline surfaces. As for the original method, neither triangulation nor derivative estimate is needed, and the computational complexity is linear. The reported numerical experiments relate to two well known test functions and con...

This paper proposes a hybrid approach by combining the evolutionary optimization based genetic algorithm (GA) and socio-political process based colonial competitive algorithm (CCA). The performance of hybrid algorithm is illustrated using standard test functions in comparison to basic CCA method. Since the CCA method is newly developed, very little research work has been undertaken to deal with...

This paper presents a hybrid particle swarm optimization algorithm (HPSO) as a modern optimization tool to solve the optimal power flow (OPF) problem. The objective functions considered are the system real power losses, fuel cost, voltage deviation and voltage stability index. The proposed algorithm makes use of the PSO, known for its global searching capabilities, to allocate the optimal contr...