Speakers

Dr. M. Jagadeeswari

Department of Mathematics, National Institute of Technology, Tiruchirappalli, India

Biography: Dr. M. Jagadeeswari was born on 1989. She graduated in Mathematics from Vellalar College for Women, Erode in 2009, M. Sc in Mathematics from Kongu Arts and Science College, Erode in 2012, M. Phil in Mathematics from Sri Vasavi College, Erode in 2015. She worked as Lecturer and Assistant Professor at Erode Kongu College of Polytechnic, Sri Vasavi College, Erode respectively. She has been awarded a Rajiv Gandhi National Fellowship by University Grants Commission during her M. Phil program. Then defended her Ph. D in 2021 at National Institute of Technology, Tiruchirappalli. Since 2021, working as an Assistant Professor at National Institute of Technology, Calicut, Maulana Azad National Institute of Technology, Bhopal, Vellore Institute of Technology, Vellore. She has published seven research articles in SCI, SCIE, Scopus indexed journals and one under process. Moreover serving as a reviewer for seven international SCI, SCIE, ESCI journals. She has taught several courses such as algebra, calculus, allied mathematics, business mathematics, discrete mathematics, basic statistics, mathematics for data science. Her Fields of research interest: Fuzzy mathematical modelling, fuzzy logic and its applications, techniques, neutrosophic set theory, fuzzy optimization, fuzzy graphs.

Title: Fuzzification And Defuzzification Of Fuzzy Logic Architecture

Abstract: In our day-to-day life, everything uses AI in someway or the other. Such a kind of AI stands for Artificial Intelligence refers to systems or machines that mimic human intelligence to perform tasks and can iteratively improve themselves based on the information they collect. To perform tasks we require to program the machines or systems. To control machines fuzzy logic system plays a significant role for both commercial and practical purposes such as maintaining and controlling machines, consumer products, providing acceptable reasoning if not accurate and helps in dealing with the uncertainty. Based on the fuzzy logic architecture, we actually use fuzzy logic in AI. Fuzzy logic architecture consists of four main parts such as rules, fuzzification, inference engine, defuzzification. Here we shall discuss vital parts fuzzification and some defuzzification techniques.