10 research outputs found

    Relations on FP-Soft Sets Applied to Decision Making Problems

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    In this work, we first define relations on the fuzzy parametrized soft sets and study their properties. We also give a decision making method based on these relations. In approximate reasoning, relations on the fuzzy parametrized soft sets have shown to be of a primordial importance. Finally, the method is successfully applied to a problems that contain uncertainties.Comment: soft application

    Generalized Operations in Soft Set Theory via Relaxed Conditions on Parameters

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    [EN] Soft set theory has been evolved as a very useful mathematical tool to handle uncertainty and ambiguity associated with the real world data based structures. Parameters with certain conditions have been used to classify the data with the help of suitable functions. The aim of this paper is to relax conditions on parameters which lead us to propose some new concepts that consequently generalize existing comparable notions. We introduce the concepts of generalized finite soft equality (gf-soft equality), generalized finite soft union (gf-soft union) and generalized finite soft intersection (gf-soft intersection) of two soft sets. We prove results involving operations introduced herein. Moreover, with the help of examples, it is shown that these operations are proper generalizations of existing comparable operations.Abbas, M.; Ali, MI.; Romaguera Bonilla, S. (2017). Generalized Operations in Soft Set Theory via Relaxed Conditions on Parameters. Filomat. 31(19):5955-5964. doi:10.2298/FIL1719955AS59555964311

    A New Extended Soft Intersection Set to M

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    Molodtsov’s soft set theory provides a general mathematical framework for dealing with uncertainty. The concepts of (M,N)-SI implicative (Boolean) filters of BL-algebras are introduced. Some good examples are explored. The relationships between (M,N)-SI filters and (M,N)-SI implicative filters are discussed. Some properties of (M,N)-SI implicative (Boolean) filters are investigated. In particular, we show that (M,N)-SI implicative filters and (M,N)-SI Boolean filters are equivalent

    Ideal Theory in Semigroups Based on Intersectional Soft Sets

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    Soft Translations and Soft Extensions of BCI/BCK-Algebras

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    The concept of soft translations of soft subalgebras and soft ideals over BCI/BCK-algebras is introduced and some related properties are studied. Notions of Soft extensions of soft subalgebras and soft ideals over BCI/BCK-algebras are also initiated. Relationships between soft translations and soft extensions are explored

    Ideal Theory in Semigroups Based on Intersectional Soft Sets

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    The notions of int-soft semigroups and int-soft left (resp., right) ideals are introduced, and several properties are investigated. Using these notions and the notion of inclusive set, characterizations of subsemigroups and left (resp., right) ideals are considered. Using the notion of int-soft products, characterizations of int-soft semigroups and int-soft left (resp., right) ideals are discussed. We prove that the soft intersection of int-soft left (resp., right) ideals (resp., int-soft semigroups) is also int-soft left (resp., right) ideals (resp., int-soft semigroups). The concept of int-soft quasi-ideals is also introduced, and characterization of a regular semigroup is discussed

    Operations on Soft Sets Revisited

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    The concept of soft sets introduced by Molodtsov is a general mathematical tool for dealing with uncertainty. Just as the conventional set-theoretic operations of intersection, union, complement, and difference, some corresponding operations on soft sets have been proposed. Unfortunately, such operations cannot keep all classical set-theoretic laws true for soft sets. In this paper, we redefine the intersection, complement, and difference of soft sets and investigate the algebraic properties of these operations along with a known union operation. We find that the new operation system on soft sets inherits all basic properties of operations on classical sets, which justifies our definitions

    A new classification technique based on hybrid fuzzy soft set theory and supervised fuzzy c-means

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    Recent advances in information technology have led to significant changes in today‟s world. The generating and collecting data have been increasing rapidly. Popular use of the World Wide Web (www) as a global information system led to a tremendous amount of information, and this can be in the form of text document. This explosive growth has generated an urgent need for new techniques and automated tools that can assist us in transforming the data into more useful information and knowledge. Data mining was born for these requirements. One of the essential processes contained in the data mining is classification, which can be used to classify such text documents and utilize it in many daily useful applications. There are many classification methods, such as Bayesian, K-Nearest Neighbor, Rocchio, SVM classifier, and Soft Set Theory used to classify text document. Although those methods are quite successful, but accuracy and efficiency are still outstanding for text classification problem. This study is to propose a new approach on classification problem based on hybrid fuzzy soft set theory and supervised fuzzy c-means. It is called Hybrid Fuzzy Classifier (HFC). The HFC used the fuzzy soft set as data representation and then using the supervised fuzzy c-mean as classifier. To evaluate the performance of HFC, two well-known datasets are used i.e., 20 Newsgroups and Reuters-21578, and compared it with the performance of classic fuzzy soft set classifiers and classic text classifiers. The results show that the HFC outperforms up to 50.42% better as compared to classic fuzzy soft set classifier and up to 0.50% better as compare classic text classifier

    Three dimensional finite element modeling, when drilling of Ti-6Al-4V

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    Finite element modeling (FEM) is widely used to optimize machining processes, to predict and analyze the cutting force, cutting temperature and other related responses. Most of the FEM studies were conducted under the two dimensional orthogonal cutting. Drilling process, which involves oblique cutting is not suitable for orthogonal cutting modelling. Therefore, an attempt to simulate a three dimensional simulation of the drilling process is required. A commercially available software called DEFORM is used to accomplish the task. The value of thrust force from the simulation is compared with the experimental results and they are both in a good agreement. Comparison of the drill temperature at TC1 and TC2 are within an error margin of 12%
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