Academic literature on the topic 'Soft Fuzzy Quotient Group'

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Journal articles on the topic "Soft Fuzzy Quotient Group"

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Dr., S. V. Manemaran *1 &. Dr. R. Nagarajan2. "APPLICATIONS OF STEP N-FUZZY FACTOR GROUP UNDER FUZZY VERSION." GLOBAL JOURNAL OF ENGINEERING SCIENCE AND RESEARCHES 6, no. 7 (2019): 105–17. https://doi.org/10.5281/zenodo.3354318.

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In this paper, we define the notion of Step N-Fuzzy Soft subgroup and investigate the condition under which a Fuzzy Soft subgroup is Step N-Fuzzy Soft subgroup. We introduce the notion of Step N-Fuzzy Soft cosets and establish their algebraic properties. We also initiate the study of Step N-Fuzzy Soft normal subgroups and quotient group with respect to Step N-Fuzzy Soft normal subgroup and prove some of their various group theoretic properties.
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S., Subramanian, and Seethalakshmi E. "CERTAIN APPLICATIONS OF P- FUZZY SOFT STRUCTURES." International Journal of Applied and Advanced Scientific Research 2, no. 2 (2017): 294–98. https://doi.org/10.5281/zenodo.1115610.

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In this paper, we investigate the notion of P-fuzzy soft intersection groups which is a generalization of that fuzzy soft groups is provided. By introducing the notion soft fuzzy cosets, soft fuzzy quotient groups based on P-fuzzy soft intersection ideals are established. Finally, isomorphism theorems of   P-fuzzy soft intersection groups related to invariant fuzzy soft sets are discussed.
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Dehghan, O. R. "Quotient bipolar fuzzy soft sets of hypervector spaces and bipolar fuzzy soft sets of quotient hypervector spaces." Journal of Algebraic Hyperstructures and Logical Algebras 4, no. 2 (2023): 67–90. http://dx.doi.org/10.61838/kman.jahla.4.2.5.

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In this paper, two related quotient structures are investigated utilizing the concept of coset. At first, a new hypervector space F/V = (F/V,\circ,\circledcirc,K) is created, which is composed of all cosets of a bipolar fuzzy soft set (F;A) over a hypervector space V . Then it will be shown that dim F/V = dim V/W, where the quotient hypervector space V/W includes all cosets of an especial subhyperspace W of V. Also, three bipolar fuzzy soft sets over the quotient hypervector space V/W are presented and in this way some new bipolar fuzzy soft hypervector spaces are defined.
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Tarmizi, Mahfuz, and Saman Abdurrahman. "GRUP FAKTOR YANG DIBANGUN DARI SUBGRUP NORMAL FUZZY." JURNAL MATEMATIKA MURNI DAN TERAPAN EPSILON 13, no. 1 (2019): 1. http://dx.doi.org/10.20527/epsilon.v13i1.1240.

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A Quotient group is a set which contains coset members and satisfies group definition. These cosets are formed by group and its normal subgroup. A set which contains fuzzy coset members is also called a quotient group. These fuzzy cosets are formed by a group and its fuzzy normal subgroup. The purpose of this research is to explain quotient groups induced by fuzzy normal subgroups and isomorphic between them. This research construct sets which contain fuzzy coset members, define an operation between fuzzy cosets and prove these sets under an operation between fuzzy coset satisfy group definiti
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Feng, Feng, Hamido Fujita, Young Bae Jun, and Madad Khan. "Decomposition of Fuzzy Soft Sets with Finite Value Spaces." Scientific World Journal 2014 (2014): 1–10. http://dx.doi.org/10.1155/2014/902687.

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The notion of fuzzy soft sets is a hybrid soft computing model that integrates both gradualness and parameterization methods in harmony to deal with uncertainty. The decomposition of fuzzy soft sets is of great importance in both theory and practical applications with regard to decision making under uncertainty. This study aims to explore decomposition of fuzzy soft sets with finite value spaces. Scalar uni-product and int-product operations of fuzzy soft sets are introduced and some related properties are investigated. Usingt-level soft sets, we define level equivalent relations and show that
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Karyati, Karyati, and Rifki Chandra Utama. "FUZZY RINGS AND ITS PROPERTIES." Jurnal Sains Dasar 5, no. 1 (2017): 32. http://dx.doi.org/10.21831/jsd.v5i1.12662.

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Abstract One of algebraic structure that involves a binary operation is a group that is defined an un empty set (classical) with an associative binary operation, it has identity elements and each element has an inverse. In the structure of the group known as the term subgroup, normal subgroup, subgroup and factor group homomorphism and its properties. Classical algebraic structure is developed to algebraic structure fuzzy by the researchers as an example semi group fuzzy and fuzzy group after fuzzy sets is introduced by L. A. Zadeh at 1965. It is inspired of writing about semi group fuzzy and
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SEZGİN, ASLIHAN, ALEYNA İLGİN, FATIMA ZEHRA KOCAKAYA, ZEYNEP HARE BAŞ, BEYZA ONUR, and FİLİZ ÇITAK. "A REMARKABLE CONTRIBUTION TO SOFT INT-GROUP THEORY VIA A COMPREHENSIVE VIEW OF SOFT COSETS." Journal of Science and Arts 24, no. 4 (2024): 905–34. https://doi.org/10.46939/j.sci.arts-24.4-a13.

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This paper aims to expand soft int-group theory by analyzing its many aspects and structural properties regarding soft cosets and soft quotient groups, which are crucial concepts of the theory. All the characteristics of soft cosets are given in accordance with the properties of classical cosets in abstract algebra, and many interesting analogous results are obtained. It is proved that if an element is in the e-set, then its soft left and right cosets are the same and equal to the soft set itself. The main and remarkable contribution of this paper to the theory is that the relation between the
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lakshmi, S. Maha, and A. Solai raju. "Hesitant Fuzzy Soft Group." International Journal of Mathematics Trends and Technology 54, no. 5 (2018): 404–14. http://dx.doi.org/10.14445/22315373/ijmtt-v54p549.

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Imtiaz, Aneeza, Umer Shuaib, Hanan Alolaiyan, Abdul Razaq та Muhammad Gulistan. "On Structural Properties of ξ -Complex Fuzzy Sets and Their Applications". Complexity 2020 (2 грудня 2020): 1–13. http://dx.doi.org/10.1155/2020/2038724.

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Complex fuzzy sets are the novel extension of Zadeh’s fuzzy sets. In this paper, we comprise the introduction to the concept of ξ -complex fuzzy sets and proofs of their various set theoretical properties. We define the notion of α , δ -cut sets of ξ -complex fuzzy sets and justify the representation of an ξ -complex fuzzy set as a union of nested intervals of these cut sets. We also apply this newly defined concept to a physical situation in which one may judge the performance of the participants in a given task. In addition, we innovate the phenomena of ξ -complex fuzzy subgroups and investi
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Ullah, Aman, Muhammad Ibrahim, and Tareq Saeed. "Fuzzy cosets in AG-groups." AIMS Mathematics 7, no. 3 (2022): 3321–44. http://dx.doi.org/10.3934/math.2022185.

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<abstract><p>In this paper, the notion of fuzzy AG-subgroups is further extended to introduce fuzzy cosets in AG-groups. It is worth mentioning that if $ A $ is any fuzzy AG-subgroup of $ G $, then $ \mu_{A}(xy) = \mu_{A}(yx) $ for all $ x, \, y\in G $, i.e. in AG-groups each fuzzy left coset is a fuzzy right coset and vice versa. Also, fuzzy coset in AG-groups could be empty contrary to fuzzy coset in group theory. However, the order of the nonempty fuzzy coset is the same as the index number $ [G:A] $. Moreover, the notions of fuzzy quotient AG-subgroup, fuzzy AG-subgroup of the
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Books on the topic "Soft Fuzzy Quotient Group"

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Fuzzy Group Theory (Studies in Fuzziness and Soft Computing). Springer, 2005.

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Book chapters on the topic "Soft Fuzzy Quotient Group"

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Perez, Ignacio Javier, Francisco Javier Cabrerizo, Sergio Alonso, Francisco Chiclana, and Enrique Herrera-Viedma. "Soft Consensus Models in Group Decision Making." In Fuzzy Logic and Information Fusion. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-30421-2_10.

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Chen, Degang, and Wenxiu Zhang. "The Lower and Upper Approximations of Fuzzy Sets in a Fuzzy Group." In Advances in Soft Computing — AFSS 2002. Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-45631-7_69.

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Maturo, Antonio, and Aldo G. S. Ventre. "Fuzzy Numbers and Consensus." In Soft Computing Applications for Group Decision-making and Consensus Modeling. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-60207-3_25.

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Dey, Balaram, Bipradas Bairagi, and Goutam Bose. "A Fuzzy-based Group Decision-making Approach for Supplier Selection." In Advances in Soft Computing Applications. River Publishers, 2023. http://dx.doi.org/10.1201/9781003425885-2.

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Krohling, Renato A., and Daniel Rigo. "Fuzzy Group Decision Making for Management of Oil Spill Responses." In Advances in Intelligent and Soft Computing. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-89619-7_1.

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Cabrerizo, Francisco Javier, Ignacio Javier Pérez, Francisco Chiclana, and Enrique Herrera-Viedma. "Group Decision Making: Consensus Approaches Based on Soft Consensus Measures." In Fuzzy Sets, Rough Sets, Multisets and Clustering. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-47557-8_18.

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Song, Ki-Young, Gerald T. G. Seniuk, and Madan M. Gupta. "An Innovative Process for Qualitative Group Decision Making Employing Fuzzy-Neural Decision Analyzer." In Advance Trends in Soft Computing. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-03674-8_42.

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Ramezani, Fahimeh, Azizollah Memariani, and Jie Lu. "A Dynamic Fuzzy Multi-criteria Group Decision Support System for Manager Selection." In Advances in Intelligent and Soft Computing. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-25658-5_33.

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Maturo, Fabrizio, and Viviana Ventre. "Consensus in Multiperson Decision Making Using Fuzzy Coalitions." In Soft Computing Applications for Group Decision-making and Consensus Modeling. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-60207-3_26.

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Sun, Shengchun, Huaiyu Pu, and Shuxin Tian. "Risk Assessment of Information System Security Based on Fuzzy Multiple Criteria Group AHP." In Advances in Intelligent and Soft Computing. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-29387-0_58.

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Conference papers on the topic "Soft Fuzzy Quotient Group"

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Villamizar-Roa, Elder J., Y. Chalco-Cano, and H. Roman-Flores. "Interval-valued functions in a quotient space." In 2015 Annual Conference of the North American Fuzzy Information Processing Society (NAFIPS) held jointly with 2015 5th World Conference on Soft Computing (WConSC). IEEE, 2015. http://dx.doi.org/10.1109/nafips-wconsc.2015.7284182.

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Das, Sujit, Mohuya B. Kar, Tandra Pal, and Samarjit Kar. "Multiple attribute group decision making using interval-valued intuitionistic fuzzy soft matrix." In 2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2014. http://dx.doi.org/10.1109/fuzz-ieee.2014.6891687.

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Yuan, Hang, Zhi Kong, Jie Zhao, and Junjun Xiong. "Applications of Time-Series Hesitation Fuzzy Soft Sets in Group Decision Making." In 2019 Chinese Control And Decision Conference (CCDC). IEEE, 2019. http://dx.doi.org/10.1109/ccdc.2019.8832856.

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Tripathy, B. K., R. K. Mohanty, and T. R. Sooraj. "On intuitionistic fuzzy soft set and its application in group decision making." In 2016 International Conference on Emerging Trends in Engineering, Technology and Science (ICETETS). IEEE, 2016. http://dx.doi.org/10.1109/icetets.2016.7603002.

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Dong, Yuanxiang, and Zhi Xiao. "Dempster-Shafer fuzzy soft sets for group decision-making based under incomplete information." In Information Science for Industry 2014. Science & Engineering Research Support soCiety, 2014. http://dx.doi.org/10.14257/astl.2014.53.41.

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Gong, Zeng-Tai, Ting Xie, Zhan-Hong Shi, and Wen-Qing Pan. "A multiparameter group decision making method based on the interval-valued intuitionistic fuzzy soft set." In 2011 International Conference on Machine Learning and Cybernetics (ICMLC). IEEE, 2011. http://dx.doi.org/10.1109/icmlc.2011.6016727.

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Sulaiman, Nor Hashimah, and Daud Mohamad. "A set theoretic similarity measure for fuzzy soft sets and its application in group decision making." In PROCEEDINGS OF THE 20TH NATIONAL SYMPOSIUM ON MATHEMATICAL SCIENCES: Research in Mathematical Sciences: A Catalyst for Creativity and Innovation. AIP, 2013. http://dx.doi.org/10.1063/1.4801129.

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Sulaiman, Nor Hashimah, and Nor Liyana Amalini Mohd Kamal. "A subsethood-based entropy for weight determination in interval-valued fuzzy soft set group decision making." In PROCEEDING OF THE 25TH NATIONAL SYMPOSIUM ON MATHEMATICAL SCIENCES (SKSM25): Mathematical Sciences as the Core of Intellectual Excellence. Author(s), 2018. http://dx.doi.org/10.1063/1.5041593.

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Poleshchuk, O., E. Komarov, and A. Darwish. "Assessment of the state of plant species in urban environment based on fuzzy information of the expert group." In 2017 XX IEEE International Conference on Soft Computing and Measurements (SCM). IEEE, 2017. http://dx.doi.org/10.1109/scm.2017.7970678.

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Pokrovskaia, N. N., and S. I. Kapitsa. "Assessment of the state of plant species in urban environment based on fuzzy information of the expert group." In 2017 XX IEEE International Conference on Soft Computing and Measurements (SCM). IEEE, 2017. http://dx.doi.org/10.1109/scm.2017.7970737.

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