In this paper a Genetic Programming algorithm for genetic association studies is reconsidered. It is shown, that the application field of the algorithm is not restricted to ge-netic association studies, but that the algorithm can also be applied to logic minimization problems. In the context of multi-valued logic minimization on incompletely specified truth tables it outperforms existing algorithms. In addition, the facilities of the algorithm in the original application field are complemented by new results and experiments. This in-cludes answers to the open questions of how to automati-cally choose the best individual in the last population and whether crossover is necessary for the algorithm
This paper proposes an algorithm to find an optimal mixture that is as close as possible to an ideal...
Tournament selection is the most frequently used form of selection in Genetic Programming (GP). Tour...
Abstract: Genetic Programming (GP) has been emerged as a promising approach to deal with classificat...
Abstract. The analysis of genetic association is useful for identifying genetic fac-tors that may co...
Abstract This paper presents a proposal for the extraction of association rules called G3PARM (Gram-...
Genetic programming (GP) is an automated method for creating a working computer program from a high-...
Abstract. Our main focus is on genetic association studies concerned with single nucleotide polymorp...
Genetic programming is a metaheuristic search method that uses a population of variable-length compu...
Abstract-- Association Rule Mining for profit patterns focuses the important issues related with bus...
Genetic algorithm is an important algorithm of association rule mining. However, there is some issue...
University of Technology, Sydney. Faculty of Engineering and Information Technology.Evolutionary alg...
The genetic algorithm (GA) is an optimization and search technique based on the principles of geneti...
Genetic algorithms and genetic programming are optimization methods in which potential solutions evo...
This paper explores the feasibility of applying genetic programming (GP) to multicategory pattern cl...
The rate of convergence and the structure of stable populations are studied for a simple, and yet no...
This paper proposes an algorithm to find an optimal mixture that is as close as possible to an ideal...
Tournament selection is the most frequently used form of selection in Genetic Programming (GP). Tour...
Abstract: Genetic Programming (GP) has been emerged as a promising approach to deal with classificat...
Abstract. The analysis of genetic association is useful for identifying genetic fac-tors that may co...
Abstract This paper presents a proposal for the extraction of association rules called G3PARM (Gram-...
Genetic programming (GP) is an automated method for creating a working computer program from a high-...
Abstract. Our main focus is on genetic association studies concerned with single nucleotide polymorp...
Genetic programming is a metaheuristic search method that uses a population of variable-length compu...
Abstract-- Association Rule Mining for profit patterns focuses the important issues related with bus...
Genetic algorithm is an important algorithm of association rule mining. However, there is some issue...
University of Technology, Sydney. Faculty of Engineering and Information Technology.Evolutionary alg...
The genetic algorithm (GA) is an optimization and search technique based on the principles of geneti...
Genetic algorithms and genetic programming are optimization methods in which potential solutions evo...
This paper explores the feasibility of applying genetic programming (GP) to multicategory pattern cl...
The rate of convergence and the structure of stable populations are studied for a simple, and yet no...
This paper proposes an algorithm to find an optimal mixture that is as close as possible to an ideal...
Tournament selection is the most frequently used form of selection in Genetic Programming (GP). Tour...
Abstract: Genetic Programming (GP) has been emerged as a promising approach to deal with classificat...