This paper describes a novel approach to performance analysis for parallel and distributed systems that is based on soft computing. We introduce the concept of performance score representing the performance of code regions that is based on fuzzy logic. We propose techniques for fuzzy-based performance classification. A novel high-level query language is designed to support the search for perfor...

Shabir and Naz in [25] introduced the notion of soft topological spaces. They defined basic notions of soft topological spaces such as open soft sets, closed soft sets, soft subspaces, soft closure, soft nbd of a soft point, soft separation axioms, soft regular spaces, soft normal spaces and they established their several properties. Min in [19] investigated some properties of such soft separat...

Soft set is a classification of elements the universe with respect to some given parameters. It new approach for modeling vagueness and uncertainty. The concept soft graph used provide parameterized point view graphs. In this paper we introduce concepts subdivision graph, power line investigate their properties.

We propose a new in-sample cross validation based method (randomized GACV) for choosing smoothing or bandwidth parameters that govern the bias-variance or fit-complexity tradeoff in 'soft' classification. Soft classification refers to a learning procedure which estimates the probability that an example with a given attribute vector is in class 1 vs class O. The target for optimizing the the tra...

This paper addresses an automatic classification of preposition types in German, comparing hard and soft clustering approaches and various windowand syntax-based co-occurrence features. We show that (i) the semantically most salient preposition features (i.e., subcategorised nouns) are the most successful, and that (ii) soft clustering approaches are required for the task but reveal quite diffe...

Fuzzy classification has become very necessary because of its ability to use simple linguistically interpretable rules and has get control over the limitations of symbolic or crisp rule based classifiers. This paper mainly deals with classification on the basis of soft computing techniques Fuzzy cognitive maps and fuzzy inference system. But the data available for classification contain some mi...

OBJECTIVE To investigate the dentoskeletal factors which may predict soft-tissue chin strain during lip closure. METHODS The pretreatment frontal and lateral facial photographs and lateral cephalograms of 209 women (aged 18-30 years) with Angle's Class I or II malocclusion were examined. The subjects were categorized by three examiners into the no-strain and strain groups according to the sof...

The relation of soft wavelet shrinkage (Donohoshrinkage) and variational denoising was discovered by Chambolle, Lucier et al. [3, 4]. Here we present an outline of this relation and give a non-convex generalization which will be related to hard wavelet shrinkage. This approach will lead to a “natural” interpolation between soft and hard shrinkage. AMS Subject Classification: 65K10, 42C40

In this paper we describe how soft computing techniques use in the problem solving approach as we did it as early in a hard computing or traditional define rule base approach. Soft Computing techniques are fuzzy logic and genetic algorithms, Artif icial Neural Networks and Expert System. Soft computing techniques have mainly two important advantages. Firstly, to solve the non-linear problems an...

In this paper, the concept of intuitionistic fuzzy soft sets is applied to residuated lattices. The notion of intuitionistic fuzzy soft filters of a residuated lattice is introduced and some related properties are investigated. Then the representations of generated intuitionistic fuzzy soft filters are established. We prove that the lattice of all intuitionistic fuzzy soft filters of a residuat...