In this paper, the effect of number and fault current limiter(FCL) location has been investigated in order to have maximum reduction of short circuit current level in all buses in a real network. To do so, the faulty buses were identified in terms of short circuit current level by computing short circuits on the desired network. Then, while the fault current limit was modeled, its optimal locat...

multiple traveling salesman problem (mtsp) is one of the most popular operation research problem and is known as combinatorial optimization problems. mtsp is an extension version of the famous and widely used problem named traveling salesman problem (tsp). because of its benefices in various domains, many researchers have tried to solve that, and many methods have proposed so far. mtsp is a np-...

clustering is the process of dividing a set of input data into a number of subgroups. the members of each subgroup are similar to each other but different from members of other subgroups. the genetic algorithm has enjoyed many applications in clustering data. one of these applications is the clustering of images. the problem with the earlier methods used in clustering images was in selecting in...

This paper presents an eficient algorithm for learning a Bayesian belief network (BBN) structure from a database, as well as providing a comparison between two BBN structure fitness functions. A Bayesian belief network is a directed acyclic graph representing conditional expectations. In this paper, we propose a two-phase algorithm. The first phase uses asymptotically correct structure learning...

This paper describes novel methods for estimating piecewise homogeneous Poisson elds based on minimum description length (MDL) criteria. By adopting a coding-theoretic approach, our methods are able to adapt to the the observed eld in an unsupervised manner. We present a parsing scheme based on xed multiscale trees (binary, for 1D, quad, for 2D) and an adaptive recursive partioning algorithm, b...

A number of optimisation problems involve the optimal grouping of a finite set of items into a number of categories. Such problems raise interesting issues in mapping solutions to strings in genetic algorithms. We argue that single string representation of solutions as permuted lists for such problems is limiting. This paper describes research into mapping a stock cutting problem where a set nu...

One of the important issues in speech emotion recognizing is selecting of appropriate feature sets in order to improve the detection rate and classification accuracy. In last studies researchers tried to select the appropriate features for classification by using the selecting and reducing the space of features methods, such as the Fisher and PCA. In this research, a hybrid evolutionary algorit...

This paper proposes an algorithm for Public Key Cryptography (PKC) using the hybrid concept of two evolutionary algorithms, Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) respectively. PSO alone are fast and easy to implement, they follow the procedures of common evolutionary algorithm and posses memory feature which is absent in GA making it more valuable. In GA whole population ...

Clustering is a widespread data analysis and data mining technique in many fields of study such as engineering, medicine, biology and the like. The aim of clustering is to collect data points. In this paper, a Cultural Algorithm (CA) is presented to optimize partition with N objects into K clusters. The CA is one of the effective methods for searching into the problem space in order to find a n...