blind source separation technique separates mixed signals blindly without any information on the mixing system. in this paper, we have used two evolutionary algorithms, namely, genetic algorithm and particle swarm optimization for blind source separation. in these techniques a novel fitness function that is based on the mutual information and high order statistics is proposed. in order to evalu...

This paper proposes the exchange market algorithm (EMA) to solve the combined economic and emission dispatch (CEED) problems in thermal power plants. The EMA is a new, robust and efficient algorithm to exploit the global optimum point in optimization problems. Existence of two seeking operators in EMA provides a high ability in exploiting global optimum point. In order to show the capabilities ...

the imperialist competitive algorithm (ica) that was recently introduced has shown its good performance in optimization problems. this algorithm is inspired by competition mechanism among imperialists and colonies, in contrast to evolutionary algorithms. this paper presents optimization of bead geometry in welding process using of ica. therefore, two case studies from literature are presented t...

A family of replicator-like dynamics, called the escort replicator equation, is constructed using information-geometric concepts and generalized information entropies and diverenges from statistical thermodynamics. Lyapunov functions and escort generalizations of basic concepts and constructions in evolutionary game theory are given, such as an escorted Fisher’s Fundamental theorem and generali...

Evolutionary game theory developed as a means to predict the expected distribution of individual behaviors in a biological system with a single species that evolves under natural selection. It has long since expanded beyond its biological roots and its initial emphasis on models based on symmetric games with a finite set of pure strategies where payoffs result from random one-time interactions ...

* The figures in Sections VII and IX were created using Dynamo [184] and VirtualLabs [92], respectively. I am grateful to Caltech for its hospitality as I completed this article, and I gratefully acknowledge financial support under NSF Grant SES-0617753.

Ever since Darwin read Malthus, the theory of evolution has benefited from the interaction of ecology with economics. Evolutionary game theory belongs to this tradition: it merges population ecology with game theory. Game theory originally addressed problems confronted by decision makers with diverging interests (for instance, firms competing for a market). The ‘players’ have to choose between ...

Ever since Darwin read Malthus, the theory of evolution has benefited from the interaction of ecology with economics. Evolutionary game theory belongs to this tradition: it merges population ecology with game theory. Game theory originally addressed problems confronted by decision makers with diverging interests (for instance, firms competing for a market). The ‘players’ have to choose between ...

this paper proposes the exchange market algorithm (ema) to solve the combined economic and emission dispatch (ceed) problems in thermal power plants. the ema is a new, robust and efficient algorithm to exploit the global optimum point in optimization problems. existence of two seeking operators in ema provides a high ability in exploiting global optimum point. in order to show the capabilities ...

neural network is one of the most widely used algorithms in the field of machine learning, on the other hand, neural network training is a complicated and important process. supervised learning needs to be organized to reach the goal as soon as possible. a supervised learning algorithm analyzes the training data and produces an inferred function, which can be used for mapping new examples.  hen...