We develop a three-step fuzzy logic-based algorithm for clustering categorical attributes, and we apply it to analyze cultural data. In the first step the algorithm employs an entropy-based clustering scheme, which initializes the cluster centers. In the second step we apply the fuzzy c-modes algorithm to obtain a fuzzy partition of the data set, and the third step introduces a novel cluster va...

Zoning the pollution of a river may be the first or even the most important step in water quality management. In order to resolve its pollution, fuzzy clustering analysis may be used whenever a composite classification of water quality incorporates mutiple parameters&#10 &#10In such cases, the technique may be used as a complement or an alternative to comprehensive assessment. In fuzzy cluster...

We present a new approach for handling fuzzy triadic data in the setting of Formal Concept Analysis. The starting point is a fuzzyvalued triadic context (K1,K2,K3, Y ), where K1,K2 and K3 are sets and Y is a ternary fuzzy relation between these sets. First, we generalise the methods of Triadic Concept Analysis to our setting and show how they fit other approaches to Fuzzy Triadic Concept Analys...

quality control plays an important role in increasing the product quality. fuzzy control charts are more sensitive than shewhart control chart. hence, the correct use of fuzzy control chart leads to producing better-quality products. this area is complex because it involves a large scope of industries, and information is not well organized. in this research, we provide a literature review of th...

Mining fuzzy association rules is the task of finding the fuzzy itemsets which frequently occur together in large fuzzy dataset, but most proposed methods may identify a fuzzy rule with two fuzzy itemsets as interesting when, in fact, the presence of one fuzzy itemsets in a record does not imply the presence of the other one in the same record. To prevent generating this kind of misleading fuzz...

Zoning the pollution of a river may be the first or even the most important step in water quality management. In order to resolve its pollution, fuzzy clustering analysis may be used whenever a composite classification of water quality incorporates mutiple parameters In such cases, the technique may be used as a complement or an alternative to comprehensive assessment. In fuzzy clustering ...

most of the researches in the domain of fuzzy number comparisons serve the fuzzy number ordering purpose. for making a comparison between two fuzzy numbers, beyond the determination of their order, it is needed to derive the magnitude of their order. in line with this idea, the concept of inequality is no longer crisp however it becomes fuzzy in the sense of representing partial belonging or de...

‎In this paper‎, ‎firstly‎, ‎we review approximation of fuzzy functions‎ ‎by fuzzy bicubic splines interpolation and present a new approach‎ ‎based on the two-dimensional fuzzy splines interpolation and‎ ‎iterative method to approximate the solution of two-dimensional‎ ‎linear fuzzy Fredholm integral equation (2DLFFIE)‎. ‎Also‎, ‎we prove‎ ‎convergence analysis and numerical stability analysis ...

The classification of fuzzy uncertain data is considered one of the most challenging issues in data analysis. In spite of the significance of fuzzy data in mathematical programming, the development of the analytical methods of fuzzy data is slow. Therefore, the current study proposes a new fuzzy data classification method based on fuzzy data envelopment analysis (DEA) which can handle strea...

First, Similarity Of Fuzzy Ontology Generation For Semantic Web, Fuzzy Formal Concept Analysis incorporates fuzzy logic into Formal Concept Analysis (FCA) to form a fuzzy concept lattice. The fuzzy ontology is an extension of the domain ontology for solving the uncertainty problems. Fuzzy Conceptual Clustering then constructs the concept hierarchy from the fuzzy concept lattice. Finally, Fuzzy ...