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For an important kind of spatial vagueness called spatial fuzziness this paper provides a conceptual and an implementation model of fuzzy spatial objects that also incorporates fuzzy geometric union, intersection, and difference operations as well as fuzzy topological predicates.
Second we introduce parameterized attribute reduction with the derived model of fuzzy rough sets.
It is shown that the model of fuzzy rough sets is sensitive to noisy samples, especially sensitive to mislabeled samples.
The ordinal structure model of fuzzy reasoning has an advantage of managing high-dimensional problem with multiple input and output variables ensuring the interpretability of the rule set.
In this paper, a computational model of fuzzy reliability focusing on solving the engineering problems with random general stress fuzzy general strength is presented.
In this paper we present a model of fuzzy spatio-temporal knowledge representation and reasoning based on high-level Petri nets.
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In spite of the impressive diversity of models of fuzzy forecasting, there is still a burning need to arrive at models that are both accurate and highly interpretable.
His current research interest focuses on Survival Analysis, Empirical Likelihood Method, Nonparametric Statistics, Analysis of ROC Curves, Bioinformatics, Monte Carlo Methods, and Statistical Modeling of Fuzzy Systems.
We noted that in the dynamic models of "fuzzy" complexes [2], just a stretch of intrinsic disordered region (IDR) could be sufficient for a protein to behave as an IUP.
The proposed integrated model of (i) Fuzzy AHP, (ii) Fuzzy Topsis (iii) Fuzzy graphical methods have been used for ranking of maintenance alternatives.
New trends in soft computing techniques, their applications, model development of fuzzy systems, integration, hybridization and adaptation are also introduced.
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