Document Type : Primary Research paper
Authors
1
Assistant Professor, PG & Research Department of Computer Science , Arignar Anna Govt. Arts College for Women, Walajapet - 632 513 , Ranipet Dist. , Tamil Nadu , India.
2
Associate Professor, Department of Computer Science and Engineering, CMR Technical Campus, Kandlakoya (V), Medchal Road, Hyderabad 501401, Telangana,India.
3
Associate Professor, Department of EEE, KPR Institute of Engineering and Technology, Avinashi Road, Coimbatore – 641407.
4
Professor, Department of Electronics and Communication Engineering, PSN College of Engineering and Technology, Tirunelveli – 627152.
5
Associate Professor, Mathematics, Sri Eshwar College of Engineering, Coimbatore-641202.
6
Associate Professor, Department of Electronics and Communication Engineering, Erode Sengunthar Engineering College, Perundurai, Erode, Tamilnadu, India – 638057.
Abstract
The instinct of human beings is very complex. The understanding of this instinct needs a
strong dimensional analysis of the knowledge of discourse. The computer systems are now
trained to realize how things operate in a real-time environment for intelligent analysis.
This effort although very progressive has a restriction. There is an intelligence gap which
makes human one step above the machine. The fuzzy logic system can be employed to
make a machine understand this intelligence gap in a better way. In other words, fuzzy
logic is a computational Intelligence technique that makes a computer understand and
think the way humans do. The fuzzy logic system is now attracting scientists and engineers
around the world since by integrating its abilities with soft computing techniques like
neuro and chaos computing, genetic algorithm, probability reasoning, and immune
networks, it can handle the problems that had not been solved before. Not only has the
fuzzy system significantly enhanced knowledge-based or expert system technology, but it
has also primarily changed the granularity of intelligence. For example, with the help of
the fuzzy logic system, industrialists of home appliances are today embedding intelligence
in specific products. The application of a fuzzy logic system has also transformed industrial
process control and enabled different product development approaches. Even though
theoretical improvements in the fuzzy logic system have mainly befallen in America and
Europe, Japanese companies have spearheaded the commercialization of the technology.
The aim of this study is two folds: first, to understand the fuzzy logic system for effective
decision making and second, to demonstrate the presence of this intelligence gap through
real-time examples. The examples are selected cautiously to illustrate and demonstrate the
applications of the fuzzy logic system for every reader.
Keywords
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