Paper Info
Title
Stochastic differential equations with fuzzy drift and diffusion
Abstract
A new framework for the fuzzification of stochastic differential equations is presented. It allows for a detailed description of the model uncertainty and the non-predictable stochastic law of natural systems, e.g. in ecosystems even the probability law of the random dynamic changes due to unobservable influences like anthropogenic disturbances or climate variation. The fuzziness of the stochastic system is modelled by a fuzzy set of stochastic differential equations which is identified with a fuzzy set of initial conditions, time-dependent drift and diffusion functions. Using appropriate function spaces the extension principle leads to a consistent theory providing fuzzy solutions in terms of fuzzy sets of processes, fuzzy states, fuzzy moments and fuzzy probabilities.
Year
DOI
Venue
2013
10.1016/j.fss.2013.02.011
Fuzzy Sets and Systems
Keywords
Field
DocType
fuzzy set,fuzzy probability,probability law,fuzzy state,fuzzy solution,non-predictable stochastic law,stochastic system,fuzzy moment,stochastic differential equation,anthropogenic disturbance,fuzzy drift
Discrete mathematics,Linear partial information,Fuzzy logic,Fuzzy measure theory,Fuzzy set,Stochastic differential equation,Continuous-time stochastic process,Stochastic partial differential equation,Fuzzy number,Mathematics
Journal
Volume
ISSN
Citations 
230,
0165-0114
0
PageRank 
References 
Authors
0.34
3
2
Name
Order
Citations
PageRank
Björn Sprungk172.12
K. Gerald van den Boogaart271.67