Fuzzy differential inclusion
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Fuzzy differential inclusion is tha culmination of Fuzzy concept and Differential inclusion introduced by Lotfi A. Zadeh which became popular.,,[1][2][3]
,
f(t,x(t)] is a fuzzy valued continuous function on eculidian space which is collection of all normal, upper semi-continous, Convex set
,Compact space , supported fuzzy subsets of .
Second order differential
The second order differential is
where
K is trapezoidal fuzzy number (-1,-1/2,0,1/2)
is a trianglular fuzzy number (-1,0,1) .
Applications
Fuzzy differential inclusion (FDI) has applications in
- Cybernetics[4]
- Artificial intelligence , Neural network,[5][6]
- Medical imaging
- Robotics
- Atmospheric dispersion modeling
- Weather forecasting
- Cyclone
- Population biology[7]
- Stochastic process , Probability theory[8]
References
- ^ "Aubin, J.-P., "Fuzzy differential inclusions," Probl. Control Inf. Theory, 19 (1), 55-67, 1990". www.sciepub.com. Retrieved 2022-10-14.
- ^ "Theory of Fuzzy Differential Equations and Inclusions". Routledge & CRC Press. Retrieved 2022-10-14.
- ^ Min, Chao; Liu, Zhi-bin; Zhang, Lie-hui; Huang, Nan-jing (2015). "On a System of Fuzzy Differential Inclusions". Filomat. 29 (6): 1231–1244. ISSN 0354-5180.
- ^ "Fuzzy differential inclusion in atmospheric and medical cybernetics" (PDF).
- ^ Tafazoli, Sina; Menhaj, Mohammad Bagher (March 2009). "Fuzzy differential inclusion in neural modeling". 2009 IEEE Symposium on Computational Intelligence in Control and Automation: 70–77. doi:10.1109/CICA.2009.4982785.
- ^ Min, Chao; Zhong, Yihua; Yang, Yan; Liu, Zhibin (May 2012). "On the implicit fuzzy differential inclusions". 2012 9th International Conference on Fuzzy Systems and Knowledge Discovery: 117–119. doi:10.1109/FSKD.2012.6234283.
- ^ "Population biology".
- ^ "Aubin, J.-P., "Fuzzy differential inclusions," Probl. Control Inf. Theory, 19 (1), 55-67, 1990". www.sciepub.com. Retrieved 2022-10-14.