Uncertainty Analysis in Tumor Model with Fuzzy Parameters

• Published in: 2009 International Conference on Computational Intelligence and Software Engineering pp. 1 - 4
• Main Authors: Esmaili, S.S., Nasrabadi, A.M.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-12-2009
• Subjects: Biological system modeling; Biomedical engineering; Differential equations; Evolution (biology); Fuzzy systems; Mathematical model; Neoplasms; Target recognition; Tumors; Uncertainty
• DOI: 10.1109/CISE.2009.5365495

Fuzzy models and fuzzy differential equations have experimented a great development in the last years, due to their application to the modelisation of systems subject to imprecision and to handle uncertainty. In this paper, a fuzzy evolution of mathematical tumor model is considered and interpreted from different point of view. Consider a crisp continuous system whose process of evolution depends on differential equations. Such a system contains a number of parameters that must be estimated. Usually point estimates are computed and used in the model. However, these point estimates typically have uncertainty associated with them. We propose to incorporate uncertainty by using fuzzy numbers as estimates of these unknown parameters. Fuzzy parameters convert the crisp system into a fuzzy system. Trajectories describing the behavior of the system become fuzzy curves.