Abstract. This paper describes a genetic algorithm for the DNA sequencing problem. The algorithm allows the input spectrum to contain both positive and negative errors as could be ...
Finding a good wavelet for a particular application and type of input data is a difficult problem. Traditional methods of wavelet deus on abstract properties of the wavelet that ca...
Planning is an artificial intelligence problem with a wide range of real-world applications. Genetic algorithms, neural networks, and simulated annealing are heuristic search met...
Han Yu, Dan C. Marinescu, Annie S. Wu, Howard Jay ...
Abstract. We discuss the problem of model selection in Genetic Programming using the framework provided by Statistical Learning Theory, i.e. Vapnik-Chervonenkis theory (VC). We pre...
One of the earliest evolutionary computation algorithms, the genetic algorithm, is applied to the noise-free BBOB 2009 testbed. It is adapted to the continuous domain by increasin...