A complex structure has many uncertain factors and how to make a more accurate analysis on the structure reliability by a method is the key in engineering calculation. Rough set theory is utilized to analyze the fuzzy, random and uncertain factors and upper and lower approximation set relation is used to calculate the value taking interval of reliability index to make reliability index analysis...

interval-valued intuitionistic fuzzy sets (ivifss) are widely used to handle uncertainty and imprecision in decision making. however, in more complicated environment, it is difficult to express the uncertain information by an ivifs with considering the decision-making preference. hence, this paper proposes a group generalized interval-valued intuitionistic fuzzy soft set (g-givifss) which conta...

Granular structure plays a very important role in the model construction, theoretical analysis and algorithm design of a granular computing method. The granular structures of classical rough sets and fuzzy rough sets have been proven to be clear. In classical rough set theory, equivalence classes are basic granules, and the lower and upper approximations of a set can be computed by those basic ...

The differences of attribute reduction and attribute core between Pawlak’s rough set model (RSM) and variable precision rough set model (VPRSM) are analyzed in detail. According to the interval properties of precision parameter b with respect to the quality of classification, the definition of attribute reduction is extended from a specific b value to a specific b interval in order to overcome ...

Interval type-2 fuzzy sets, each of which is characterized by the footprint of uncertainty, are a very useful means to depict the linguistic information in the process of decision making. In this article, we investigate the group decision making problems in which all the linguistic information provided by the decision makers is expressed as interval type-2 fuzzy decision matrices where each of ...

Rough data envelopment analysis (RDEA) evaluates the performance of the decision making units (DMUs) under rough uncertainty assumption. In this paper, new discussion regarding RDEA is extended. The RSBM model is proposed by integrating SBM model and rough set theory. The process of reaching solution is presented and this model is applied to efficiency evaluation of the DMUs with uncertain ...

Data granulation is considered a good tool of decision making in various types of real life applications. The basic ideas of data granulation have appeared in many fields, such as interval analysis, quantization, rough set theory, Dempster-Shafer theory of belief functions, divide and conquer, cluster analysis, machine learning, databases, information retrieval, and many others. Some new topolo...