Background and Objectives: Stock price prediction has become one of the interesting and also challenging topics for researchers in the past few years. Due to the non-linear nature of the time-series data of the stock prices, mathematical modeling approaches usually fail to yield acceptable results. Therefore, machine learning methods can be a promising solution to this problem. Methods: In this...

Article history: Received July 2 2013 Received in revised format September 7 2013 Accepted September 15 2013 Available online September 23 2013 The present work proposes a multi-objective improved teaching-learning based optimization (MO-ITLBO) algorithm for unconstrained and constrained multi-objective function optimization. The MO-ITLBO algorithm is the improved version of basic teaching-lear...

distribution centers (dcs) play important role in maintaining the uninterrupted flow of goods and materials between the manufacturers and their customers.this paper proposes a mathematical model as the bi-objective capacitated multi-vehicle allocation of customers to distribution centers. an evolutionary algorithm named non-dominated sorting ant colony optimization (nsaco) is used as the optimi...

Genetic algorithms (GAs) are biologically motivated adaptive systems which have been used, with varying degrees of success, for function optimization. In this study, an abstraction of the basic genetic algorithm, the Equilibrium Genetic Algorithm (EGA), and the GA in turn, are reconsidered within the framework of competitive learning. This new perspective reveals a number of different possibili...

In this paper, a high-performance optimal fractional emotional intelligent controller for an Automatic Voltage Regulator (AVR) in power system using Cuckoo optimization algorithm (COA) is proposed. AVR is the main controller within the excitation system that preserves the terminal voltage of a synchronous generator at a specified level. The proposed control strategy is based on brain emotional ...

in this paper, the problem of layout optimization for x-bracing of steel frames is studied using the ant system (as). a new design method is employed to share the gravity and the lateral loads between the main frame and the bracings according to the requirements of the ibc2006 code. an algorithm is developed which is called optimum steel designer (osd). an optimization method based on an approx...

Current optimization algorithms are designed for problems in which explicit fitness functions are provided. They can not be directly applied to problems where fitness functions do not exist, such as a situation where a user can interact with the computer by providing vague feedbacks instead of specific fitness. This paper proposes a population-based algorithm to solve such an optimization probl...