{"type":"ScholarlyArticle","title":"A Qualitative-Fuzzy Framework for Nonlinear Black-Box System Identification","authors":[{"name":"Riccardo Bellazzi","slug":"riccardo-bellazzi","given":"Riccardo","family":"Bellazzi","affiliation":"Informatica e Sistemistica Univ. Pavia"},{"name":"Raffaella Guglielmann","slug":"raffaella-guglielmann","given":"Raffaella","family":"Guglielmann","affiliation":"Istituto di Analisi Numerica"},{"name":"Liliana Ironi","slug":"liliana-ironi","given":"Liliana","family":"Ironi","affiliation":"Istituto di Analisi Numerica C.N.R. via Ferrata 1 27100 Pavia , Italy via Abbiategrasso 209 27100 Pavia , Italy via Abbiategrasso 209 27100 Pavia , Italy"}],"abstract":"This paper presents a novel approach to nonlinear black-box system identification which combines Qualitative Reasoning ( QR) methods with fuzzy logic systems. Such a method aims at building a good initialization of a fuzzy identifier, so that it will converge to the inputoutput relation which captures the nonlinear dynamics of the system. FUzzy inference procedures should be initialized with a rule-base predefined by the human expert: when such a base is not available or poorly defined, the inference procedure becomes extremely inefficient. Our method aims at solving the problem of the construction of a meaningful rulebase: fuzzy rules are automatically generated by encoding the knowledge of the system dynamics described by the outcomes of its qualitative simulation. Both efficiency and robustness of the method are demonstrated by its application to the identification of the kinetics of Thiamine (vitamin BI) and its phosphoesters in the cells of the intestine tissue.","doi":null,"url":"https://ijcai.org/proceedings/1999/148","pdf":"https://ijcai.org/proceedings/1999/0148.pdf","markdown":"https://ijcai.org/proceedings/1999/148.md","bibtex":"https://ijcai.org/proceedings/1999/bibtex/148","volume":{"slug":"1999","title":"Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 1999","url":"https://ijcai.org/proceedings/1999/","year":1999,"location":"Stockholm, Sweden","dates":"","editors":"Thomas Dean","isbn":"","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":"Qualitative Reasoning and Diagnosis","track":"Qualitative Reasoning and Diagnosis","number":148,"pages":{"first":1041,"last":1045},"keywords":[],"videos":[],"references":[{"position":1,"raw":"[Barada and Singh, 1998] S. Barada and H. Singh. Gen- erating optimal adaptive fuzzy-neural models of dy- namical systems with application to control. IEEE Trans. Systems, Man, and Cybernetics, 28(3) :371- 391, 1998.","title":"Generating optimal adaptive fuzzy-neural models of dynamical systems with application to control","authors":"S Barada, H Singh","year":"1998","venue":"IEEE Trans. Systems, Man, and Cybernetics","doi":null,"url":null,"internal_url":null},{"position":2,"raw":"[Jang, 1993] J. Jang. Anfis: Adaptive network based fuzzy inference system. IEEE Trans. on Systems, Man and Cybernetics, 23:665-685, 1993.","title":"Anfis: Adaptive network based fuzzy inference system","authors":"J Jang","year":"1993","venue":"IEEE Trans. on Systems, Man and Cybernetics","doi":null,"url":null,"internal_url":null},{"position":3,"raw":"[Khannah, 1990] T. Khannah. Foundations of neural networks. Addison-Wesley, Reading, MA, 1990.","title":"Foundations of neural networks","authors":"T Khannah","year":"1990","venue":null,"doi":null,"url":null,"internal_url":null},{"position":4,"raw":"[Kim and Mendel, 1995] H.M. Kim and J.M . Mendel. Fuzzy basis functions: Comparison with other basis functions. IEEE Trans. Fuzzy Systems, 3:158-168, 1995.","title":"Fuzzy basis functions: Comparison with other basis functions","authors":"H M Kim, J M Mendel","year":"1995","venue":"IEEE Trans. Fuzzy Systems","doi":null,"url":null,"internal_url":null},{"position":5,"raw":"[Kuipers, 1994] B. J. Kuipers. Qualitative Reasoning: modeling and simulation with incomplete knowledge. MIT Press, Cambridge MA, 1994.","title":"Qualitative Reasoning: modeling and simulation with incomplete knowledge","authors":"B J Kuipers","year":"1994","venue":null,"doi":null,"url":null,"internal_url":null},{"position":6,"raw":"[Mamdani, 1974] E.H. Mamdani. Applications of fuzzy algorithms for simple dynamic plant. Proc. lEE, 121(12):1585-1588, 1974.","title":"Applications of fuzzy algorithms for simple dynamic plant","authors":"E H Mamdani","year":"1974","venue":"Proc. lEE","doi":null,"url":null,"internal_url":null},{"position":7,"raw":"[Rindi et al., 1980] G. Rindi, C. Patrini, V. Comincioli, and C. Reggiani. Thiamine content and turnover rates of some rat nervous region, using labeled thiamine as a tracer. Brain Res., 181:369-380, 1980.","title":"Thiamine content and turnover rates of some rat nervous region, using labeled thiamine as a tracer","authors":"G Rindi, C Patrini, V Comincioli, C Reggiani","year":"1980","venue":"Brain Res","doi":null,"url":null,"internal_url":null},{"position":8,"raw":"[Shen and Leitch, 1993] Q. Shen and R.R. Leitch. Fuzzy qualitative simulation. IEEE Tran. on Systems, Man and Cybernetics, 23:1038-1061, 1993.","title":"Fuzzy qualitative simulation","authors":"Q Shen, R R Leitch","year":"1993","venue":"IEEE Tran. on Systems, Man and Cybernetics","doi":null,"url":null,"internal_url":null},{"position":9,"raw":"[Vescovi and Trave-Massuyes, 1992] M.R. Vescovi and Louise Trave-Massuyes. A constructive approach to qualitative fuzzy simulation. In Proc. 6th Interna- tional Workshop on Qualitative Reasoning, pages 268- 280, Edinburgh, 1992.","title":"A constructive approach to qualitative fuzzy simulation","authors":"M R Vescovi, Louise Trave-Massuyes","year":"1992","venue":"Proc. 6th International Workshop on Qualitative Reasoning","doi":null,"url":null,"internal_url":null},{"position":10,"raw":"[Wang, 1994] L.X. Wang. Adaptive Fuzzy Systems and Control: design and stability analysis. Englewood Cliff, NJ:Prentice--Hall, University of California at Berkeley, 1994.","title":"Adaptive Fuzzy Systems and Control: design and stability analysis","authors":"L X Wang","year":"1994","venue":null,"doi":null,"url":null,"internal_url":null},{"position":11,"raw":"[Zeng and Singh, 1996] X.J. Zeng and M.G. Singh. Ap- proximation accuracy analysis of fuzzy systems as functions approximators. IEEE Transactions on Fuzzy Systems, 4(1):44-63, 1996.","title":"Approximation accuracy analysis of fuzzy systems as functions approximators","authors":"Singh Zeng, X J Zeng, M G Singh","year":"1996","venue":"IEEE Transactions on Fuzzy Systems","doi":null,"url":null,"internal_url":null}],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}