Fuzzy set map comparison offers a novel approach to map comparison (Hagen 2003). The approach is specifically aimed at categorical raster maps and applies fuzzy set techniques, accounting for fuzziness of location and fuzziness of category, to create a similarity map as well as an overall similarity statistic: the Fuzzy Kappa. To date, the calculation of the Fuzzy Kappa (or K-fuzzy) has not bee...

Plenty of researches have been carried out, focusing on the measures of distance, similarity, and correlation between intuitionistic fuzzy sets (IFSs).However, most of them are single-valued measures and lack of potential for efficiency validation.In this paper, a new vector valued similarity measure for IFSs is proposed based on OWA operators.The vector is defined as a two-tuple consisting of ...

We present a method for segmenting white matter as well as the gray matter structures from diffusion tensor magnetic resonance images (DT-MRI). The segmentation is done evolving a set of coupled level set functions. The zero level set of each level set function forms a surface in 3D that is driven by the region-based force including all tensors belonging to a certain region. The region-based fo...

In this paper, we give a new similarity measure on npn-soft set theory which is the extension of correlation measure of neutrosophic refined sets. By using the similarity measure we propose a new method for decision making problem. Finally, we give an example for diagnosis of diseases could be improved by incorporating clinical results and other competing diagnosis in npn-soft environment..

In a recent article, Tversky questioned the application of geometric models to similarity data and proposed an alternative set-theoretic approach. He suggested that geometric models are inappropriate because the similarity data may violate the metric assumptions underlying such models. In addition, he demonstrated that the stimulus context and the nature of the experimental task can affect the ...

This paper introduces “class-aware similarity hashes” or “classprints,” which are an outgrowth of recent work on similarity hashing. The approach builds on the notion of context-based hashing to create a framework for identifying data types based on content and for building characteristic similarity hashes for individual data items that can be used for correlation. The principal benefits are th...

Molodtsov [35] initiated the soft set theory, which can be used as a generic mathematical tool for dealing with uncertainty. Maji [30] defined the concept of neutrosophic soft set which is based on a combination of the neutrosophic set and soft set models. In this paper, we give the notion of neutrosophic soft set with a new style and present some algebraic properties. We define several distanc...

Many data mining algorithms developed recently are based on inductive learning methods. Very few are based on similarity-based learning. However, similarity-based learning accrues advantages, such as simple representations for concept descriptions, low incremental learning costs, small storage requirements, etc. We present a similarity-based learning method from databases in the context of roug...

We begin the paper studying the axioms that the indicators of the grade of inclusion of a fuzzy set in another fuzzy set must satisfy. Next, we present an expression of such indicator, ®rst for fuzzy sets and then for interval-valued fuzzy sets, analyzing in both cases their main properties. Then, we suggest an expression for the similarity measure between interval-valued fuzzy sets. Besides, w...