Evolutionary algorithms have been recognized to be suitable for extracting approximate solutions of multi-objective problems because of their capability to evolve a set of non-dominated solutions distributed along the Pareto frontier‎. ‎This paper applies an evolutionary optimization scheme‎, ‎inspired by Multi-objective Invasive Weed Optimization (MOIWO) and Non-dominated Sorting (NS) strategi...

The main purpose of this paper is to solve an inverse random differential equation problem using evolutionary algorithms. Particle Swarm Algorithm and Genetic Algorithm are two algorithms that are used in this paper. In this paper, we solve the inverse problem by solving the inverse random differential equation using Crank-Nicholson's method. Then, using the particle swarm optimization algorith...

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...

Fuzzy clustering methods are conveniently employed in constructing a fuzzy model of a system, but they need to tune some parameters. In this research, FCM is chosen for fuzzy clustering. Parameters such as the number of clusters and the value of fuzzifier significantly influence the extent of generalization of the fuzzy model. These two parameters require tuning to reduce the overfitting in the...

This study is devoted to discrete sizing optimization of truss structures employing an efficient discrete evolutionary meta-heuristic algorithm which uses the Newton gradient-based method as its updating scheme and it is named here as Newton Meta-heuristic Algorithm (NMA). In order to enable the NMA population-based meta-heuristic to effectively explore the discrete design space, a term contain...

We present quantitative models for the selection pressure on cellular evolutionary algorithms structured as a ring of cells. We obtain results for synchronous and asynchronous cell update policies. Theoretical results are in agreement with experimental values and show that the selection intensity can be controlled by using different update methods.

Human language, over its evolutionary history, has emerged as one of the fundamental defining characteristic of the modern man. However, this milestone evolutionary process through natural selection has not left any ’linguistic fossils’ that may enable us to trace back the actual course of development of language and its establishment in human societies. Lacking analytical tools to fathom the cr...

In this study, a new approach isintroduced to solve Blasius differential equation using of ImperialistCompetitive Algorithm (ICA). This algorithm is inspired by competitionmechanism among Imperialists and colonies and has demonstrated excellent capabilitiessuch as simplicity, accuracy, faster convergence and better global optimumachievement in contrast to other evolutionary algorithms. The obta...

Clustering is one of the known techniques in the field of data mining where data with similar properties is within the set of categories. K-means algorithm is one the simplest clustering algorithms which have disadvantages sensitive to initial values of the clusters and converging to the local optimum. In recent years, several algorithms are provided based on evolutionary algorithms for cluster...

  Fuzzy time series have been developed during the last decade to improve the forecast accuracy. Many algorithms have been applied in this approach of forecasting such as high order time invariant fuzzy time series. In this paper, we present a hybrid algorithm to deal with the forecasting problem based on time variant fuzzy time series and particle swarm optimization algorithm, as a highly effi...