By D. Dubois, H. Prade, L. Ughetto (auth.), Nikhil R. Pal, Michio Sugeno (eds.)
It is our nice excitement to welcome you all to the 2002 AFSS foreign convention on Fuzzy structures (AFSS 2002) to be held in Calcutta, the nice urban of pleasure. AFSS 2002 is the ?fth convention within the sequence initiated by way of the Asian Fuzzy platforms Society (AFSS). AFSS 2002 is together being prepared by means of theIndianStatisticalInstitute(ISI)andJadavpurUniversity(JU). Likeprevious conferencesinthisseries,wearesure,AFSS2002willprovideaforumforfruitful interplay and trade of principles among the individuals from all around the globe. the current convention covers all significant features of sentimental computing reminiscent of fuzzy good judgment, neural networks, genetic algorithms together with either theories and functions. Wehopethismeetingwillbeenjoyableacademicallyandotherwise. we're grateful to the participants of the overseas application Committee and the realm Chairs for extending their help in quite a few varieties to make a robust technical software. every one submitted paper used to be reviewed by way of no less than 3 referees, and often times the revised types have been back checked via the ref- ees. due to this difficult screening technique lets pick out basically approximately 50% of the submitted papers. We back convey our honest due to all referees for doing a very good task. we're chuffed to notice that 19 di?erent nations from everywhere in the globe are represented via the authors, thereby making it a really inter- tional convention. we're proud to have a listing of extraordinary audio system together with Profs. Z. Pawlak, J. Bezdek, D. Dubois, and T. Yamakawa.
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Extra resources for Advances in Soft Computing — AFSS 2002: 2002 AFSS International Conference on Fuzzy Systems Calcutta, India, February 3–6, 2002 Proceedings
Reasoning with fuzzy default values’, in Proceedings 15th IEEE International Symposium on Multiple-valued logic, Kingston, Ont. , 1985, pp. 191-197. 7. , ‘Similarity based approximate reasoning’, in methodologies for the conception, design and application of intelligent systems, Proc. IIZUKA’96, 4th Int. Conf. on Soft Computing, IIZUKA, Japan, 1996, pp. 414-417. 8. Ray, ‘Reasoning with vague default’, Fuzzy Sets and Systems, 1997, vol. 91, no. 3, pp. 327-338. 9. 13, pp. 81-132. 10. 31, pp. 99-112.
It is also very easy to verify that if the observation coincides with one of the antecedents then the conclusion will be exactly the corresponding consequence. Finally, we remark that multivariable antecedents can be handled analogously as the transformation described in this section affects only the consequent part. Common combined antecedent sets (and observation) can be calculated from the corresponding antecedents (observation) of each variable using Minkowski-type distance, where the weights are identical to 1.
Z 1 and Z 2 have no common component X = Z 0 × Z 1 × Z 2 . The rule base will have the following structure: Xi. Consequently, Interpolation in Hierarchical Rule-Bases with Normal Conclusions R1 : R0 : If z 0 is D1 then use R1 If z 0 is D2 then use If R2 z1 is A11 37 R2 : then y is B11 If z1 is A12 then y is B12 If z2 is A21 then y is B21 If z2 is A22 then y is B22 Let us assume that the observation on X is A* and its projections are: A0* = A * Z 0 , A1* = A * Z 1 , A2* = A * Z 2 . Using the Fundamental Equation, the two subconclusions, obtained from the two sub-rule bases R1 and R2 are: KH 1* bk = (1 − λ1k )b11k + λ1k b21k , and KH bk2* = (1 − λ 2k )b12k + λ 2k b22k respectively.
Advances in Soft Computing — AFSS 2002: 2002 AFSS International Conference on Fuzzy Systems Calcutta, India, February 3–6, 2002 Proceedings by D. Dubois, H. Prade, L. Ughetto (auth.), Nikhil R. Pal, Michio Sugeno (eds.)