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Prediction of Autism Severity Level in Bangladesh Using Fuzzy Logic: FIS and ANFIS

  • Rahbar Ahsan
  • Tauseef Tasin Chowdhury
  • Wasit Ahmed
  • Mahrin Alam Mahia
  • Tahmin Mishma
  • Mahbubur Rahman Mishal
  • Rashedur M. RahmanEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 833)

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.

Keywords

Autism; ASD Fuzzy Severity Fuzzification Rule generation Defuzzification FIS ANFIS Triangular function 

Notes

Acknowledgments

First, we would like to thank Proyash, Institute of Special Education, Alokito Shishu, Seher Autism Center for helping us on data collection. We want to thank psychiatrist from Proyash for guiding us while making the rule set. Finally, we want to thank all the teachers who had participated in the survey.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Rahbar Ahsan
    • 1
  • Tauseef Tasin Chowdhury
    • 1
  • Wasit Ahmed
    • 1
  • Mahrin Alam Mahia
    • 1
  • Tahmin Mishma
    • 1
  • Mahbubur Rahman Mishal
    • 1
  • Rashedur M. Rahman
    • 1
    Email author
  1. 1.Department of Electrical and Computer EngineeringNorth South UniversityDhakaBangladesh

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