The assessment and selection of green supplier development programs are an intriguing and functional research subject. This paper proposes a group decision-making approach considering possibilistic statistical concepts under uncertainty to assess green supplier development programs (GSDPs) via interval-valued fuzzy sets (IVFSs). Possibility theory is employed to regard uncertainty by IVFSs. A n...

introduction linking resolution global climate models to local scale as a micro climatic process is a significant issue. recently, attempts have been made by the climatology scientists to develop dynamics and statistical downscaling methods to express climate change at a local and regional scale. two general techniques are been used for downscaling of the output of general circulation models (g...

Starting from the pioneering publication of Lot Zadeh in 1965 [55], fuzzy sets have been applied to many elds in which uncertainty plays a key role. Medicine, often on the borderline between science and art, is an excellent exponent: vagueness, linguistic uncertainty, hesitation, measurement imprecision, natural diversity, subjectivity { all these are prominently present in medical diagnosis. W...

1. Introduction In statistical analysis, it is important to discuss both uncertainty due to

This paper considers the application of method of percentile matching available in statistical theory of estimation for estimating the parameters involved in uncertainty distributions. An empirical study has been carried out to compare the performance of the proposed method with the method of moments and the method of least squares considered by Wang and Peng (J. Uncertainty Analys. Appl. 2, (2...

Computer-Intensive methods for estimation assessment provide valuable information concerning the adequacy of applied probabilistic models. The bootstrap method is an extensive computational approach to uncertainty estimation based on resampling and statistical estimation. It is a powerful tool, especially when only a small data set is used to predict the behaviour of systems or processes. This ...

Geographical data is inherently uncertain. There are a variety of sources that contribute to this uncertainty. Operations performed on data during an analysis will most likely only increase this uncertainty. To understand the uncertainty in the results of an analysis, requires information about the uncertainty in the input data, and some idea about how various analysis operations propagate and ...