Similarity-Based Fuzzy Reasoning for Radiation Fog Prediction.

Date of Submission

December 2008

Date of Award

Winter 12-12-2009

Institute Name (Publisher)

Indian Statistical Institute

Document Type

Master's Dissertation

Degree Name

Master of Technology

Subject Name

Computer Science


Electronics and Communication Sciences Unit (ECSU-Kolkata)


Ray, Kumar Sankar (ECSU-Kolkata; ISI)

Abstract (Summary of the Work)

Conventional modus ponens is not sufficient enough to draw conclusion when the antecedent of the implication rule does not exactly match the given fact. Zadeh’s generalization of modus ponens in fuzzy logic can overcome this drawback. Thus, the consequent can still be drawn even if the fact does not match with the antecedent of the IF-THEN rule. Zadeh’s generalized modus ponens uses CRI(COMPOSITIONAL RULE OF INFERENCE) to get the conclusion. Many existing fuzzy reasoning methods are based on Zadeh’s CRI, which requires setting up a relation between the antecedent and the consequent part. There are some other fuzzy reasoning methods which do not use Zadeh’s CRI. Among them, The similarity-based fuzzy reasoning methods, which make use of the degree of similarity between a given fact and the antecedent of the rule to draw a conclusion. In this work first we consider an approach for prediction of radiation fog by Zadeh’s fuzzy reasoning.For this purpose we have developed a fuzzy rule based approach for the prediction where we can capture the large experience and intuition of an expert fog predictor. But the results we got were not satisfactory after the execution of this process. So we have adapted the similarity based reasoning in which we measure the degree of similarity between the given fact(sensor values) and the antecedent part of the rules and draw the conclusion which is much better than the method mentioned previously. Prediction of radiation fog helps airlines maintain their schedule and also helps in avoiding run way accidents.


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Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.


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