Different approaches of fuzzy structure identification in mining medical diagnosis rules

2004 IEEE Conference on Cybernetics and Intelligent Systems

Volumn , Issue , 2004, Pages 562-567

  Kilic, Kemal ^a   Uncu, Ozge ^b   Turksen, I B ^c  

^a SABANCI UNIVERSITY   (Turkey)

^b MIDDLE EAST TECHNICAL UNIVERSITY   (Turkey)

^c UNIVERSITY OF TORONTO   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; APPROXIMATION THEORY; COMPUTER SIMULATION; DATA REDUCTION; DIAGNOSIS; FUNCTIONS; IDENTIFICATION (CONTROL SYSTEMS); NONLINEAR PROGRAMMING;

AACHEN APHASIA TEST (AAT); FUZZY REASONING; NUMBER OF DATA (ND);

FUZZY SETS;

EID: 11244297044     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (9)

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2. H. Axer, J. Jantzen, G. Berks, D. Südfeld and D. G. v.Keyserlingk, "Aphasia classification using neural networks," Proc. of ESIT, Aachen, Germany, 2000, pp. 111-115
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9. O. Uncu, I. B. Turksen and K. Kilic, "LOCALM-FSM: A new fuzzy system modelling approach using a two-step fuzzy inference mechanism based on local fuzziness level," IFSA World Congress, Istanbul, Turkey, 2003, pp. 191-194