Application of fuzzy modeling to detect mathematical learning disorder

Abstract

Fuzzy logic has proved to be a powerful tool for decision-making, and to handle and manipulate imprecise and noisy data. Major advantage of this theory is that it allows the natural description, in linguistic terms, of problems that should be solved rather than in terms of relationships between precise numerical values. This paper discusses the use of fuzzy classification to cognitive science field for classifying children having mathematical learning disorder. We have developed a fuzzy model with six fuzzy attributes from six identified dyscalculia testing domains. The output of fuzzy model is classification of children as pure, probabilistic and no dyscalculic. Our findings have been scientifically supported by the neuropsychological results that the range of 3–6% of the population suffers from severe mathematical learning disorders.