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Traditional genetic algorithms use only one crossover and one mutation operator to generate the next generation. The chosen crossover and mutation operators are critical to the success of genetic algorithms. Different crossover or mutation operators, however, are suitable for different problems,...
This paper documents an early effort to develop an experimental, collaborative data analysis technique for learning classifiers from a collection of heterogeneous datasets distributed over a network. The proposed technique makes use of a scalable evolutionary algorithm, called the GEMGA to...
Optimization theory and method profoundly impact numerous engineering designs and applications. The gradient descent method is simpler and more extensively used to solve numerous optimization problems than other search methods. However, the gradient descent method is easily trapped into a local...
This paper introduces a new fast, effective and practical model structure construction algorithm for a mixture of experts network system utilising only process data. The algorithm is based on a novel forward constrained regression procedure. Given a full set of the experts as potential model...
In this paper we describe the use of model-based diagnosis for locating bugs in hardware designs. Nowadays hardware designs are written in a programming language. We restrict our view to hardware designs written in a subset of the commonly used hardware description language VHDL. This subset...
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