while sophisticated analytical methods like morgenstern-price or finite elementmethods are available for more realistic analysis of stability of slopes, assessment of the exactvalues of soil parameters is practically impossible. uncertainty in the soil parameters arisesfrom two different sources: scatter in data and systematic error inherent in the estimate of soilproperties. hence, stability o...

The objective of this paper is to compare probabilistic models and fuzzy set models for design against uncertainty when there is limited information about the statistics of the uncertainty or modeling error. First, we compare the axioms of probabilistic and fuzzy set methods and the rules governing the arithmetic operations that these methods use. Then, we compare the two methods in designing f...

The concept of fuzzy random variable has been applied in several papers to model the present value of life insurance liabilities. It allows the fuzzy uncertainty of the interest rate and the probabilistic behaviour of mortality to be used throughout the valuation process without any loss of information. Using this framework, and considering a triangular interest rate, this paper develops closed...

The binary states, i.e., success or failed state assumptions used in conventional reliability are inappropriate for reliability analysis of complex industrial systems due to lack of sufficient probabilistic information. For large complex systems, the uncertainty of each individual parameter enhances the uncertainty of the system reliability. In this paper, the concept of fuzzy reliability...

We distinguish three types of uncertainty: the probabilistic, the quantum and the fuzzy uncertainty. In these three contexts, we use diierent mathematical models to describe the event structures | the Boolean, the quantum and the fuzzy logics. We deene states in a uniform way as valuations. Let us ask the following question: If a; b are two elements of a (Boolean, quantum, fuzzy, resp.) logic L...

supply chain network design decisions are among the strategic decisions of supply chain management which play significant role on the efficient performance of the supply chain. however, there are two challenging factors which may have great impact on the supply chain performance. these factors are on the one hand disruptions and their attendant damages and on the other hand uncertain nature of ...

While sophisticated analytical methods like Morgenstern-Price or finite elementmethods are available for more realistic analysis of stability of slopes, assessment of the exactvalues of soil parameters is practically impossible. Uncertainty in the soil parameters arisesfrom two different sources: scatter in data and systematic error inherent in the estimate of soilproperties. Hence, stability o...

Uncertainty analysis of future system operation is the key feature of current study. This paper shows that how subjective differences in representing fuzzy inputs can affect the final outputs. We consider a confined range of forecasted samples in terms of fuzzy membership functions as well as the range of historical forecasting errors in terms of probability density functions. On this basis, th...

In this paper, the connection between Menger probabilistic norms and H"{o}hle probabilistic norms is discussed. In addition, the correspondence between probabilistic norms and Wu-Fang fuzzy (semi-) norms is established. It is shown that a probabilistic norm (with triangular norm $min$) can generate a Wu-Fang fuzzy semi-norm and conversely, a Wu-Fang fuzzy norm can generate a probabilistic norm.