Expressions of Rock Joint Roughness Coefficient Using Neutrosophic Interval Statistical Numbers
نویسندگان
چکیده
منابع مشابه
Expressions of Rock Joint Roughness Coefficient Using Neutrosophic Interval Statistical Numbers
In nature, the mechanical properties of geological bodies are very complex, and their various mechanical parameters are vague, incomplete, imprecise, and indeterminate. However, we cannot express them by the crisp values in classical probability and statistics. In geotechnical engineering, we need to try our best to approximate exact values in indeterminate environments because determining the ...
متن کاملScale Effect and Anisotropy Analyzed for Neutrosophic Numbers of Rock Joint Roughness Coefficient Based on Neutrosophic Statistics
In rock mechanics, the study of shear strength on the structural surface is crucial to evaluating the stability of engineering rock mass. In order to determine the shear strength, a key parameter is the joint roughness coefficient (JRC). To express and analyze JRC values, Ye et al. have proposed JRC neutrosophic numbers (JRC-NNs) and fitting functions of JRC-NNs, which are obtained by the class...
متن کاملExpression and Analysis of Joint Roughness Coefficient Using Neutrosophic Number Functions
In nature, the mechanical properties of geological bodies are very complex, and its various mechanical parameters are vague, incomplete, imprecise, and indeterminate. In these cases, we cannot always compute or provide exact/crisp values for the joint roughness coefficient (JRC), which is a quite crucial parameter for determining the shear strength in rock mechanics, but we need to approximate ...
متن کاملCorrelation Coefficient of Interval Neutrosophic Set
In this paper we introduce for the first time the concept of correlation coefficients of interval valued neutrosophic set (INS for short). Respective numerical examples are presented.
متن کاملCorrelation Coefficient Between Fuzzy Numbers Based On Central Interval
When we deal with crisp data, it is very common to find the correlation between variables. Here, we propose a method to calculate the correlation coefficient for fuzzy data, but rather than defining the correlation on the intuitionistic fuzzy sets like most of the previous works, we adopt the method from central interval. This interval can be used as a crisp set approximation with respect to a ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Symmetry
سال: 2017
ISSN: 2073-8994
DOI: 10.3390/sym9070123