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To solve the problems of GACD, a Genetic Algorithm with Chromosome Differentiation, (sampling-without-replacement, mating-with-the-best-chromosome, and the-unreachable-result), a kind of Genetic Algorithm with Sex Differentiation, named GASD, is proposed. Then an in-depth theoretical analysis is conducted to evaluate the performance of the algorithm. Finally, a mixed solution, which simultaneously...
This paper proposed a real-coded chaotic quantum immune genetic algorithm (RCIQGA) based on the chaotic and coherent characters of Q-bits, and also introduces immune concepts and methods. In this algorithm, real chromosomes are inversely mapped to Q-bits in the solution space Q-bits probability guided real cross and chaos mutation are used to real chromosomes evolution and searching. Meanwhile immune...
A new adaptive mutation method, which uses the information of relative importance of chromosomes and alleles, is proposed for genetic algorithm(GA). In each generation, suitable chromosomes for mutation are automatically choosed based on cumulative distribution function of chromosomes fitness, without requiring to set the mutation probability anymore. After selecting chromosomes for mutation, the...
A new genetic algorithm, combined cultivating with migrating operators (CMGA), is proposed. Cultivating operator can make gene segments of chromosomes keep superior characteristics at a higher probability. A new migrating schema with directed direction guided by illumination information is discussed, and it can overcome the blindness and invalidity in genetic operations. We focus on key factors of...
Bandyopadhyay and Pal proposed an improved genetic search strategy, GACD, involving partitioning the chromosomes into two classes, and defining a restricted form of the crossover operator between the two classes. The GACD can be applied to many multi-dimensional pattern recognition problems. However, their GACD suffered from two kinds of problems, i.e. "sampling-without-replacement" and...
In this paper we describe a method to evolve biologically inspired motion detection systems utilizing artificial neural networks (ANN's). Previously, the evolution of neural networks has focused on feed-forward neural networks or networks with predefined architectures. The purpose of this paper is to present a novel method for evolving neural networks with no predefined architectures to solve various...
We use probabilistic Boolean networks to simulate the pathogenesis of Dengue Hemorraghic Fever (DHF). Based on Chaturvedi's work, the strength of cytokine influences are modeled stochastically as inducement probabilities. We use an aggregated function approach to derive the DHF Infection Model. Two basins of attractors are observed with synchronous updating; the Null Infection cycle attractor shows...
We use probabilistic Boolean networks to simulate the pathogenesis of Dengue Hemorraghic Fever (DHF). Based on Chaturvedi's work, the strength of cytokine influences are modeled stochastically as inducement probabilities. We use an aggregated function approach to derive the DHF Infection Model. Two basins of attractors are observed with synchronous updating; the Null Infection cycle attractor shows...
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