Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
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Amino acid sequences are usually described using categorical variables which are difficult to change to a numerical form. We compare two numerical coding methods in polyproline type II secondary structure predictions, the frequently used binary vector coding method and our new real value coding method based on the PAM250 substitution table which consists of amino acid mutation information. The real value coding method has good properties such as space saving and illustrative form. Our first results are almost comparable to the results of traditional binary vector coding method.