Fuzzy differential inclusions in atmospheric and medical cybernetics.
Uncertainty management in dynamical systems is receiving attention in artificial intelligence, particularly in the fields of qualitative and model based reasoning. Fuzzy dynamical systems occupy a very important position in the class of uncertain systems. It is well established that the fuzzy dynamical systems represented by a set of fuzzy differential inclusions (FDI) are very convenient tools for modeling and simulation of various uncertain systems. In this paper, we discuss about the mathematical modeling of two very complex natural phenomena by means of FDIs. One of them belongs to the atmospheric cybernetics (the term has been used in a broad sense) of the genesis of a cyclonic storm (cyclogenesis), and the other belongs to the bio-medical cybernetics of the evolution of tumor in a human body. Since a discussion of the former already appears in a previous paper by the first author, here, we present very briefly a theoretical formalism of cyclone formation. On the other hand, we treat the latter system more elaborately. We solve the FDIs with the help of an algorithm developed in this paper to numerically simulate the mathematical models. From the simulation results thus obtained, we have drawn a number of interesting conclusions, which have been verified, and this vindicates the validity of our models.
Majumdar
Kausik Kumar
KK
Electronics and Communications Sciences Unit, Indian Statistical Institute, Calcutta, 700108, India.
Majumder
Dwijesh Dutta
DD
D000465:Algorithms; D000818:Animals; D001272:Atmosphere; D002455:Cell Division; D003198:Computer Simulation; D003491:Cybernetics / Q000379:methods*; D004190:Disasters; D017143:Fuzzy Logic; D006801:Humans; D008954:Models, Biological; D009369:Neoplasms / Q000473:pathology* / Q000503:physiopathology*