Fuzzy differential inclusion
Fuzzy differential inclusion is the extension of differential inclusion to fuzzy sets introduced by Lotfi A. Zadeh.[1][2]
with
Suppose is a fuzzy valued continuous function on Euclidean space. Then it is the collection of all normal, upper semi-continuous, convex, compactly supported fuzzy subsets of .
Second order differential
The second order differential is
where , is trapezoidal fuzzy number , and is a trianglular fuzzy number (-1,0,1).
Applications
Fuzzy differential inclusion (FDI) has applications in
- Cybernetics[3]
- Artificial intelligence, Neural network,[4][5]
- Medical imaging
- Robotics
- Atmospheric dispersion modeling
- Weather forecasting
- Cyclone
- Pattern recognition
- Population biology[6]