Abstract
In 1965 Lofti Zadeh published his paper on fuzzy set theory , putting it forward as a way of more closely realising the human thought process. Many systems developed to aid human activities have been based on definitive , yes/no, type decision making processes. An example is the way all computers are based on the binary logic system where only two possible and separate logic levels are allowed, a logic 1 or logic 0. However, we know from everyday experience that humans think in terms of vague linguistic categories, for example, the weather is fairly good today. "Fairly good" represents a vague category that can be represented by a fuzzy set which allows values to belong to the set by a varying degree from 0 up to 1. The grade of membership is not a probability , it is a measure of the compatibility of an object with the concept represented by the fuzzy set.
Since Zadeh proposed his theory many areas of applications have been considered to assess the suitability of applying fuzzy set theory. Areas include fuzzy logic and approximate reasoning, expert systems, pattern recognition, fuzzy decision making in economics and medicine and fuzzy control. However, it is in the area of fuzzy logic control that most success has been achieved.
Recommended Citation
Manley, Raymond
(2000)
"Fuzzy Logic and Neural Networks - a Glimpse of the Future,"
The ITB Journal:
Vol. 1:
Iss.
1, Article 4.
doi:10.21427/D7D333
Available at:
https://arrow.tudublin.ie/itbj/vol1/iss1/4
DOI
10.21427/D7D333