Prediction of autism severity level in Bangladesh using fuzzy logic: FIS and ANFIS

4Citations
Citations of this article
7Readers
Mendeley users who have this article in their library.
Get full text

Abstract

A type of neurodevelopment disorder also known as autism is currently more visible than before among the people of Bangladesh. Some research works could be found on autism but very few papers are guided to measure the severity level. Hence, this research focuses on attaining the severity level of autism using fuzzy methods like Mamdani Fuzzy Inference System (MAMFIS) and Adaptive Neuro-Fuzzy Inference System (ANFIS). A survey has been conducted on autistic children to find the severity level. The levels used in this research are low, medium, high. A comparative study of those two methods has been reported in this paper. By using ANFIS we get better accuracy compared to the FIS model.

Cite

CITATION STYLE

APA

Ahsan, R., Chowdhury, T. T., Ahmed, W., Mahia, M. A., Mishma, T., Mishal, M. R., & Rahman, R. M. (2019). Prediction of autism severity level in Bangladesh using fuzzy logic: FIS and ANFIS. In Advances in Intelligent Systems and Computing (Vol. 833, pp. 201–210). Springer Verlag. https://doi.org/10.1007/978-3-319-98678-4_22

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free