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Uncertainty Handling using Fuzzy Logic in Rule Based Systems

초록

영어

In real world computing environment, the information is not complete, precise and certain, making very difficult to derive an actual decision. To deal with processing and modeling of such information, fuzzy techniques are applied to exercise the proper conclusion. This paper focuses on the basics of Fuzzy Logic and its application in Rule Based Systems to make them capable to handle the real world problems. Also, different research issues associated with FRBSs have been discussed. Also, a traffic control system is proposed and evaluated using MATLAB.

목차

Abstract
 1. Introduction
 2. Basic Concepts of Fuzzy Logic
  2.1 Universe of Discourse
  2.2 Representation of Fuzzy Sets
  2.3 Algebraic Operations on Fuzzy Sets
  2.4 Support Set
  2.5  -cut of the Fuzzy Set
 3. Fuzzy Rule Based Systems (FRBS)
  3.1 Mamdani Fuzzy Rule – Based Systems
  3.2 TSK Fuzzy Rule Based Systems
  3.3 Research Issues and Challenges in Fuzzy Rule Based Systems
  3.1 Context Adaptation
  3.2 Interpretability Accuracy Trade-Off
  3.3 Fuzzy Rule Selection
  3.4 Optimization of Membership Function and Scaling Function
  3.5 Fuzzy Partition Granularity
 4. Proposed Urban Traffic Control System
  4.1 Definition of Membership Functions
  4.2 Knowledge Base Definition
  4.3 System Evaluation
  4.4 Result Analysis
 5. Conclusion & Future Scope
 References

저자정보

  • Poonam Department of Information Technology, Northern India Engineering College
  • Surya Prakash Tripathi Department of Computer Science & Engineering, Institute of Engineering & Technology (A Constituent College of GBTU)
  • Praveen Kumar Shukla Department of Computer Science & Engineering, Babu Banarasi Das University

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