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Distribution fitting is a widely recurring problem in different fields such as telecommunication, finance and economics, sociology, physics, etc. Standard methods often require solving difficult equations systems or investments in specialized software. The paper presents a new approach to distribution fitting that exploits Genetic Algorithms in order to simultaneously identify the distribution type...
Linear Linkage Encoding (LLE) is a powerful encoding scheme utilized when genetic algorithms (GAs) are applied to grouping problems. It discards the redundancy of other traditional encoding schemes. However, some genetic operators are quite costly in terms of computational time when LLE is utilized. In this study, two supplementary encoding schemes Linear Linkage Encoding with Ending Node Links (LLE-e)...
Genetic algorithm and particle swarm optimization are two methods which can be used to find the global extremum of cost functions. The solely performance of each method and their specific characteristics in finding the global extremum have been giving the idea of hybridization of these two methods to many researchers. In this paper a new hybrid algorithm named Serial Genetic Algorithm and Particle...
Techniques exist to synthesize software architecture using genetic algorithms that employ transformations based on mutations and crossover. In this paper, we demonstrate that complementary crossover can significantly improve this technique. We study two versions of complementary crossover, one in which parents are selected so that they complement each other but the genes are inherited randomly from...
One of the major issues concerning the Artificial Neural Networks (ANNs) design is a proper adjustment of the weights of the network. There have been a number of studies comparing the performance of evolutionary and gradient based ANNs learning. But the results of the studies, sometime conflicting to each other although the same and standard dataset development had been used. Motivated by this finding,...
This paper proposes a novel image fusion method that uses continuous Genetic Algorithm (CGA). Image fusion provides a single output image from a set of input images, captured from different viewing conditions, by different sensors, and at different times. Image fusion can be divided into three processing levels: pixel, feature and decision. Genetic algorithms are a nonlinear optimization technique...
The optimal product line design problem consists of predicting the acceptance of new products in the market, prior of the actual production phase. It requires a unique blend of techniques and resources as it deals with multiple parameters and hard optimization problems. This paper proposes a service oriented architecture which outlines the basic features that a marketing decision support system should...
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