Assessing Morningness of a Group of People by Using Fuzzy Expert System and Adaptive Neuro Fuzzy Inference Model

• Published in: Control, Computation and Information Systems pp. 47 - 56
• Main Authors: Biswas, Animesh, Majumder, Debasish, Sahu, Subhasis
• Format: Book Chapter
• Language: English
• Published: Berlin, Heidelberg Springer Berlin Heidelberg 2011
• Series: Communications in Computer and Information Science
• Subjects: ANFIS; Chronotypology; Fuzzy Expert System; Mamdani Fuzzy Inference System; Morningness; rMEQ
• ISBN: 3642192629; 9783642192623
• ISSN: 1865-0929; 1865-0937
• DOI: 10.1007/978-3-642-19263-0_6

In this paper two computational systems, one is based on fuzzy logic system and other is based on adaptive neuro fuzzy inference system (ANFIS), are developed for assessing morningness of a group of people and the result is compared for finding the best system in the assessment process. In fuzzy rule based system, the linguistic terms for assessing morningness are quantified by using fuzzy logic and a fuzzy expert system is developed. On the other side, an ANFIS model is generated to assess data for training and testing the model in accordance with a preference scale adopted to quantify the responses of subjects for a reduced version of Morningness-Eveningness Questionnaire (rMEQ). The result reflects that ANFIS is able to assess morningness better than fuzzy expert inference system.