# application of fuzzy automata's theory

Topics: Fuzzy logic, Decision theory, Formal language Pages: 12 (1323 words) Published: September 22, 2014
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TERMPAPER
OF
APPLICATION OF FUZZY AUTOMATA THEORY
Formal Languages and Automation Theory (CAP632)
?Submitted To: - ?Submitted By: -
Miss. Kiran Sharma Name: -Dheeraj Sharma Section: -D1207 Roll No:-RD1207A09 Regd No: -11207869 dheerajsharma7777@yahoo .com
INDEX

S.NO
TOPIC
PAGE NO
1.
Abstract
3
2.
Introduction
3-4
3.
Formulation of fuzzy automata
4
4.
Fuzzy automata as model learning system
4-5
5.
Applications of fuzzy automata theory
6-9
6.
Objectives of fuzzy automata theory
9-10
7.
Scope of fuzzy automata theory
10
8.
Conclusion
11
9.
References
11

ABSTRACT
This term paper provides an overview of topic application of fuzzy automata theory. In this term paper we discuss all formulation of fuzzy automata and also working on fuzzy automata as model of learning system. In this paper we discuss some applications comes under in fuzzy automata theory. Theory of fuzzy sets and fuzzy theory logic has been applied to problem in various fields like topologies, game theory etc also we discuss or described in this term paper. And in this term paper we have also discuss its future work and where we use its applications. There is a deep reason to study fuzzy automata: several languages are fuzzy by nature (e.g.: the language containing words in which many letter “a” occur. That type of stuff comes under in fuzzy automata and all these terms and useful application we all discuss now.

INTRODUCTION
Mathematical models in classical computation automata have been an important area in theoretical computer science. The basic idea in the formulation of a fuzzy automaton is that, unlike the classical case, the fuzzy automaton can switch from one state to another one to certain (truth) degree. Thus, researching fuzzy automaton with ability of processing fuzzy processes is need. Even when a system input at a time is missing, the system can work accurately. Fuzzy automata are the machines accepting fuzzy regular language. This language is a feature of fuzzy language and is described by fuzzy regular expression. Many decision- making and problem- solving tasks are too complex to be understood quantitatively, however people succeed by using knowledge that is imprecise rather than precise. Fuzzy automata theory resembles human reasoning in its use of approximate information and uncertainty to generate decision. In here we simulate real world problems such as decision making problem in urban traffic system, where a condition of jam can have cumulative effect on city’s commutation structure.

FORMULATON OF FUZZY AUTOMATA
A fuzzy automaton is a quintuple (Q, X, Y, µ, ω), where:
Q nonempty finite set (the set of internal states),
X nonempty finite set (the set of input states),
Y nonempty finite set (the set of output states).
µ is a fuzzy subset of Q x X x Q, i .e., µ: Q * X * Q [0,1], ω is a fuzzy subset of Q x X x Y, i. e., ω: Q * X * Y [0, 1]. In here u is called the fuzzy transition function and w the fuzzy output function. In here: Q= {q1, q2 …qn} X= {x1, x2 …xp}

Y= {y1, y2 ...yr).

FUZZY AUTOMATA AS MODEL LEARNING SYSTEM
The proposed model represents a non supervised learning system if a proper performance evaluator can be selected. The learning section primarily consists

Figure 1: Basic Learning Model
of composite fuzzy automaton. The performance evaluator serves as an unreliable “teacher” who tries to teach the “student” (the learning section and decision maker) to make correct decisions. The decision executed by...

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