‎financial market modeling and prediction is a difficult problem and drastic changes of the price causes nonlinear dynamic that makes the price prediction one of the most challenging tasks for economists‎. ‎since markets always have been interesting for traders‎, ‎many traders with various beliefs are highly active in a market‎. ‎the competition among two agents of traders‎, ‎namely trend follo...

Evolutionary game theory has grown into an active area of research that bridges concepts from biology, evolution, nonlinear dynamics, and game theory. The mechanisms necessary to conduct an evolutionary analysis of games are presented. Relations between evolutionary stable strategies and Nash equilibria are considered. Replicator dynamics are developed and applied to three relevant games. The a...

Kin selection theory based on the concept of inclusive fitness is often presented as a general approach that can deal with many aspects of evolutionary dynamics. Here we show that this is not the case. Instead, inclusive fitness considerations rest on fragile assumptions, which do not hold in general. The quantitative analysis of kin selection relies completely on inclusive fitness theory. No o...

Sediment rating curve (SRC) is a conventional and a common regression model in estimating suspended sediment load (SSL) of flow discharge. However, in most cases the data log-transformation in SRC models causing a bias which underestimates SSL prediction. In this study, using the daily stream flow and suspended sediment load data from Shalman hydrometric station on Shalmanroud River, Guilan Pro...

Emotions obviously play an important role in human behavior. This study seeks to determine why emotions may have evolved. It is speculated that one’s genes seek to influence the individual beyond merely the construction of the individual’s body at birth. Game theoretic methods have been employed, to search for Evolutionary Stable Strategies (ESSs) that would make it more likely for an individua...

The creation of mathematical, as well as qualitative (or rule-based), models is diffiult, time-consuming, and expensive. Recent developments in evolutionary computation hold out the prospect that, fir many problems of practical import, machine learning techniques can be used to discover useful models automatically. These prospects are particularly bright, we believe, for such automated discover...

This paper focuses on multi-objective designing of multi-machine Thyristor Controlled Series Compensator (TCSC) using Strength Pareto Evolutionary Algorithm (SPEA). The TCSC parameters designing problem is converted to an optimization problem with the multi-objective function including the desired damping factor and the desired damping ratio of the power system modes, which is solved by a SPEA ...

In this paper, I have described Genetic Algorithm for combinatorial data leading to establishment of mathematical modeling for Information Theory. The paper describes GA (Genetic Algorithm) in light of information theory and then derives Mathematical Framework covering but not limited to Big Data. This framework is a boon to any domain that has to harness data explosion like neurobiology, stati...

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...

The purpose of this article is to review the literature on the topic of deterministic vehicle routing problem (VRP) and to give a review on the exact and approximate solution techniques. More specifically the approximate (meta-heuristic) solution techniques are classified into: tabu search, simulated annealing, genetic algorithm, evolutionary algorithm, hybrid algorithm, and Ant Colony Opti...