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Table of Contents:

Remarks

The concept of FL was first presented by Zadeh, which is able to translate our qualitative knowledge into reasoning systems. Hybrid intelligent Phased

Mission System (PMS) inspired by the proposed quantum is designed with the help of FL. As far as PMS is concerned, we used FL as a problem-solving tenancy system approach. FL provides a decent way to solve location-related queries that are ambiguous and contain inaccurate input information. Also, instead of applying a mathematical model to a specific system, FL incorporates rule-based IF A AND В TF1EN C flows to solve position-based queries. Therefore, it incorporates rule-based tactics into the proposed PMS framework to resolve location-related queries in real time and provide confidentiality protection for end users' current location. Also in FL, the concept of a fuzzy reasoning system is used. This is basically the process of formulating a mapping from a given input to an expected output. It consists of IF-THEN rules, logical operations and membership functions. FIS can be implemented using two techniques: Mamdani type and Sugeno type techniques. The fuzzy reasoning system process consists of five steps: fuzzifying input variables, applying fuzzy operators (AND or OR), inference from predecessors (predecessors) to results, teaming results through rules, and fuzzifying. In the proposed PMS framework, we integrate the concept of FIS and FL. Location-based query forwarding and response is implemented in a conceptual way of FIS.

Exercise

  • 1. Distinguish between fuzzification and defuzzification.
  • 2. What is the main difference between probability and fuzzy logic?
  • 3. What is the primary reason that fuzzy logic has wilt one of the most successful tools in developing sophisticated system?
  • 4. Describe any one method of defuzzification.
  • 5. Discuss various set-theoretic operations on fuzzy sets with relevant examples.

References

Herrera, Francisco, and Enrique Herrera-Viedma. "Linguistic decision analysis: Steps for solving decision problems under linguistic information." Fuzzy Sets and Systems 115, no. 1 (2000): 67-82.

Russell, Bertrand. "Vagueness." The Australasian Journal of Psychology and Philosophy 1, no. 2 (1923): 84-92.

Schwartz, Jack "The harmful effects of mathematics in science," In Ernest Nagel, Patrick Suppes, and Alfred Tarski (Eds), Logic Methodology and Philosophy of Science, pp. 231-235. Standford University Press, Standford, CA (1962).

Schwartz, Jack. "The pernicious influence of mathematics on science." In Studies in Logic and the Foundations of Mathematics, vol. 44, pp. 356-360. Elsevier, Amsterdam, Netherlands (1966).

Triantaphyllou, Evangelos. "Multi-criteria decision making methods." In: Multi- Criteria Decision Making Methods: A Comparative Study, pp. 5-21. Springer, Boston, MA (2000).

Wang, Liang, Reza Langari, and John Yen. "Identifying fuzzy rule-based models using orthogonal transformation and backpropagation." In Fuzzy Theory Systems, pp. 187-204. Academic Press, Cambridge, MA (1999).

Zadeh, Lotfi Asker. "Fuzzy sets." Information and Control 8, no. 3 (1965): 338-353.

Zadeh, Lotfi Asker. "The concept of a linguistic variable and its application to approximate reasoning, memorandum ERL-M411, Berkeley." (1973).

Zadeh, Lotfi Asker. "Fuzzy logic=computing with words." IEEE Transactions on Fuzzy Systems 4, no. 2 (1996): 103-111. DOI: 10.1109/91.493904.

 
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