In this paper, the performance of the various fuzzy based algorithms for medical image segmentation is presented. Fuzzy c-means (FCM) algorithm has proved its effectiveness for image segmentation. However, still it lacks in getting robustness to noise and outliers, especially in the absence of prior knowledge of the noise. To overcome this problem, different types of fuzzy algorithms are introd...

The interface between combinatorial optimization and fuzzy sets-based methodologies is the subject of very active and increasing research. In this context we describe FANS, a fuzzy adaptive neighborhood search optimization heuristic that uses a fuzzy valuation to qualify solutions and adapts its behavior as a function of the search state. FANS may also be regarded as a local search framework. W...

Abstract Multi-label feature selection, a crucial preprocessing step for multi-label classification, has been widely applied to data mining, artificial intelligence and other fields. However, most of the existing selection methods dealing with mixed have following problems: (1) These rarely consider importance features from multiple perspectives, which analyzes not comprehensive enough. (2) sel...

Obtaining a weaker condition that preserves some inspired topological properties is always desirable. As result, we introduce the concept of infra-fuzzy topology, which subset family degrades fuzzy topology by omitting closedness under arbitrary unions. Fundamental spaces are investigated, including open and closed sets, interior closure operators, boundary set. It not possible to expect latter...

Fuzzy rough set (FRS) has a great effect on data mining processes and the fuzzy logical operators play key role in development of FRS theory. In order to generalize theory more complicated environments, we firstly propose four types neighborhood based covering by overlap functions their implicators this paper. Meanwhile, derived coverings from an original are defined equalities among function-b...