Sugeno

The ANFIS neurofuzzy controller was implemented by Jang (1993) and employs a Takagi-Sugeno-Kang (TSK) fuzzy inference system. The basic ANFIS architecture is shown in Figure 10.31. 

Sugeno, M. (ed.) (1985) Industrial Applications of Euzzy Control, Elsevier Science Publishers BV, North-Holland. 

M. Koike, S. Futaguchi, S. Takahashi, K. Sugeno, Biopharmaceutical Characterization of 450191-S, a Ring-Opened Derivative of 1,4-Benzodiazepine. II. Evidence for Reduced First-Pass Extraction by Rat Liver , Drug Metab. Dispos. 1988, 16, 609-615. 

Sugeno H, Takebayashi Y, Higashimoto M, Ogura Y, Shibukawa G, Kanzaki A et al. Expression of copper-transporting P-type adenosine triphosphatase (ATP7B) in human hepatocellular carcinoma. Anticancer Res 2004 24 1045-8. 

The second broad framework for dealing with uncertainty—fuzzy measure theory—was founded by Sugeno in 1974, even though some basic ideas of fuzzy measures had already been recognized by Choquet in 1953. Fuzzy measure theory is an outgrowth of classical measure theory, which is obtained by replacing the additivity requirement of classical measures with the weaker requirements of monotonicity (with respect to set inclusion) and continuity (or semicontinuity) of fuzzy measures. 

M. Sugeno, Theory of Fuzzy Integrals and its Applications," Ph.D. dissertation, Tokyo Institute of Technology, Tokyo, 1974. 

M. Sugeno et al., Proceedings of International Fuzzy Engineering Symposium 1991, pp. 1120-1121, 1991, Yokohama, Japan. 

Mizojiri K, Norikura R, Takashima A, Tanaka H, Yoshimori T, Inazawa K, Yukawa T, Okabe H, Sugeno K. Disposition of moxalactam and N-methyl-tetrazolethiol in rats and monkeys. Antimicrob Agents Chemother 1987 31(8) 1169-76. 

Matsubara, T., M. Koike, A. Touchi, Y. Tochino, and K. Sugeno (1976). Quantitative determination of cytochrome P-450 in rat liver homogenate. Anal. Biochem. 75, 596-603. 

Sugeno, K., Matsubara, H., "The Amino Acid Sequence of Scenedesmus... 

Tagaki and Sugeno suggested rule-based systems that involve fuzzy sets only in the premise part and the consequence part consists of a nonfuzzy function, for example,... 

T. Hasegawa, N. Sugeno, A. Takeda, M. Matsuzaki-Kobayashi, A. Kikuchi, K. Furukawa, T. Miyagi, and Y. Itoyama, Role of Neu4L siahdase and its substrate ganghoside GD3 in neuronal apoptosis induced by catechol metabolites, FEBSLett., 581 (2007) 406-412. 

The described inference method, due to Mamdani (1974), is the most popular other inference methods for fuzzy systems based on linguistic rules are Sugeno models and Tsukamoto models (Mamdani 1974 Sugeno 1985). 

Sugeno M (1985) Industrial applications of fuzzy control. Elsevier Science, New York... 

Dragan K (2002) Design of adaptive takagi-sugeno-kang fuzzy models. Appl Soft Comput 2(2) 89-103... 

O. Mendoza, P. Melin, G. Licea, A hybrid approach for image recognition combining type-2 fuzzy logic, modular neural networks and the Sugeno integral. Inf. Sci. 179, 2078-2101 (2009)... 

H. Taguchi, K. Shioura and M. Sugeno, Nozzle tip for spinning glass fiber having deformed cross section and a plurality of projections, U. S. Patent 5,462,571, October 31,1995. 

Motohashi Y, Sekigami T, Sugeno N (1997) J Mater Process Technol 68 229... 

M, and B are abbreviations for small, medium, and big, respectively. We used the phase clusterization method reported by Konstantin (68) and Kishimoto (66). First, the phase of culture growth was determined from the pattern of the state variable classified by each membe ip function. Second, the probability that the measured state fails into the phase was calculated. Third, the value of the operative variable was calculated for each situa tion. Sugeno s third inferraice method (69) was used for defuzzification. 

Sugeno M. Fuzzy seigyo, 1st ed. Tokyo Nikkan Kogyo Shinbunsha, 1988 86-90. 

For the purpose of explaining the ALM algorithm, the Sugeno and Yasukawa (1993) dummy non-linear static problem (equation (1)) with two input variables (a i and xi) and one output (y) is solved by this method. 

The results show that the path of figure 2f is better than the path of figure2e. The selected paths should be saved because these are implicit non-linear functions. The p>aths can be saved as a look-up table, heteroassociative neural network memory (Fausset, 1994) or fuzzy curve expressions such as Takagi and Sugeno method (TSM) (Takagi and Sugeno, 1985). Look up tables are most convenient method and it is used for path saving in this example (Step 5). 

Partitioning of multi-dimensional space is a combinatorial problem There is no theoretical approach for it therefore, heuristic search methods are used (Takagi and Sugeno 1985). 

SUGENO, M. and Yasukawa, T., 1993, A fuzzy-logic based approach to qualitative modeling. IEEE Transactions on Fuzzy Systems, 1, pp. 7-31. 

Takagi, T. and SuGENO, M., 1985, Fuzzy identification of systems and its apvplications to modeling and control. IEEE Transactions on Systems, Man, and Cybernetics, SMC-15,... 

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