Interactive genetic algorithms are effective methods applied into the conceptual design of car console in order to better cater to the customer’s individualized demands for product design. In traditional interactive genetic algorithms, users’ fatigue problem restricts the population size. We propose individual fitness estimation method based on artificial neural network to reduce user fatigue p...

A trinary-phased array, in which a phase quantization unit of phase shifters is 120 degrees is examined. The phase quantization unit of 120 degrees is the roughest value in practical phased array applications. Despite its rough phase quantization, the sidelobe level of less than −9 dB is attained by a genetic algorithm approach. key words: phased array, trinary phase shifter sidelobe reduc-

The process of identifying the optimal parameters for an optimization algorithm or a machine learning one is a costly combinatorial problem because it involves the search of a large, possibly infinite, space of candidate parameter sets. Our work compares grid search with a simple genetic algorithm when used to find the optimal parameter setting for an ID3 like learner operating on given dataset...

We present various learning methods for RBF networks. The standard gradient-based learning is augmented by the weighted norm adaptation. The three-step learning algorithm uses different unsupervised learning algorithms for setting the centroids. Two possible combinations with genetic learning algorithm are considered as well. All learning variants are thoroughly compared on two benchmark tasks....

The bankruptcy prediction models have long been proposedas a key subject in finance. The present study, therefore, makes aneffort to examine the corporate bankruptcy prediction through employmentof the genetic algorithm model. Furthermore, it attempts to evaluatethe strategies to overcome the drawbacks of ordinary methods forbankruptcy prediction through application of genetic algorithms. Thesa...

In this paper we analyze the cryptanalysis of the simplified data encryption standard algorithm using meta-heuristics and in particular genetic algorithms. The classic fitness function when using such an algorithm is to compare n-gram statistics of a the decrypted message with those of the target message. We show that using such a function is irrelevant in case of Genetic Algorithm, simply beca...

In this article we discuss our approach to the evolution of wandering behavior in a multi agent system (MAS). Our discussion covers the various aspects of the system setup, the performed experiments and the interpretation of the results observed. Utilizing a genetic algorithm (GA) and multi layer perceptrons (ANN) we show how wandering behavior is developed provided a single fitness criterion. ...