Texture Classification Using a Novel, Soft-Set Theory Based Classification Algorithm

Mushrif, Milind M.; Sengupta, Somnath; Ray, Ajoy Kumar

doi:10.1007/11612032_26

Cited by 84 publications

(42 citation statements)

References 6 publications

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“…They also applied these notions to the problem of medical diagnosis in medical systems. The algebraic structure of soft set theory and soft topological spaces dealing with uncertainties has also been studied by many researchers [1], [3], [6][7], [9][10][11][12][13][14][15], [20], [22][23][24]. Recently, Ackgoz and Tas [2] introduced a binary soft set over two initial universal sets and a parameter set and explored its basic structures.…”

Section: Introductionmentioning

confidence: 99%

On Some Structures of Binary Soft Topological Spaces

Hussain¹

2017

HJMS

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We initiate binary soft topological spaces which are, in fact, generalization of soft topological spaces in broader sense. The basic structures and concepts of binary soft topological spaces using binary soft points are studied and their fundamental properties are explored. Examples and counter examples are also provided to efficiently describe the presented notions and results. The results, discussed in this paper, are basic and provide an introductory platform but potentially useful research in theoretical as well as applicable directions.

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Section: Introductionmentioning

confidence: 99%

On Some Structures of Binary Soft Topological Spaces

Hussain¹

2017

HJMS

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“…Maji and Roy [8] introduced the definition of reduct-soft-set and described the application of soft set theory as a problem in decision-making. Mushrif et al [9] proposed a new classification algorithm of the natural textures, which was based on the notions of soft set theory. Zou and Xiao [10] presented data analysis approaches of soft set under incomplete information.…”

Section: Introductionmentioning

confidence: 99%

A hybrid method for decision making with dependence & feedback under incomplete information

Chen

Zou

2016

SHS Web of Conferences

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This paper presents a hybrid method to tackle multiple criteria decision making problems with incomplete weight information in the context of fuzzy soft sets. In order to determine the weights of criteria, we develop a comprehensive two-stage framework. Stage One: We first define the distance between two fuzzy soft numbers. Next, we establish an optimization model based on ideal point of attribute values, by which the attribute weights can be determined. Stage Two: To get the global weights, we use fuzzy cognitive maps to depict the dependent and feedback effect among criteria. Next, we require constructing fuzzy soft set to decide the desirable alternative. Finally, a case study is given to clarify the proposed approach of this paper.

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“…Also an attempt was made by Kostek [10] to assess sound quality based on a soft set approach. Mushrif et al [11] presented a novel method for the classification of natural textures using the notions of soft set theory. The topological structures of set theories dealing with uncertainties were first studied by Chang [12].…”

Section: Introductionmentioning

confidence: 99%

Soft Generalized Closed Sets with Respect to an Ideal in Soft Topological Spaces

Mustafa¹,

Sleim²

2014

Appl. Math. Inf. Sci.

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Abstract:A soft ideal on a non empty set X is a non empty collection of soft subsets of X with heredity property which is also closed under finite unions. The concept of soft generalized closed sets in soft topological spaces was introduced by Kannan [1]. In this paper, we introduce and study the concept of soft generalized closed sets with respect to a soft ideal, which is the extension of the concept of soft generalized closed sets.

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Texture Classification Using a Novel, Soft-Set Theory Based Classification Algorithm

Cited by 84 publications

References 6 publications

On Some Structures of Binary Soft Topological Spaces

On Some Structures of Binary Soft Topological Spaces

A hybrid method for decision making with dependence & feedback under incomplete information

Soft Generalized Closed Sets with Respect to an Ideal in Soft Topological Spaces

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