Abstract:A clear understanding of risk factors is important to develop appropriate prevention and control strategies for infection caused by such pathogens as Salmonella Typhimurium. In this study, there are 91 risk factors that nonlinearly contribute to the Salmonella Typhimurium infection and many of them are not of significance. It is very important to automatically extract a factor subset with those important risk factors. This paper proposes a genetic algorithm for factor subset extraction in conjunction with neur… Show more
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