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Relevant bibliographies by topics / Interval valued fuzzy neutrosophic soft set

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Academic literature on the topic 'Interval valued fuzzy neutrosophic soft set'

Author: Grafiati

Published: 2 June 2025

Last updated: 31 July 2025

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Journal articles on the topic "Interval valued fuzzy neutrosophic soft set"

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Broumi, Said, and Flornetin Smarandache. "Interval-Valued Neutrosophic Soft Rough Sets." International Journal of Computational Mathematics 2015 (January 19, 2015): 1–13. http://dx.doi.org/10.1155/2015/232919.

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We first defined interval-valued neutrosophic soft rough sets (IVN-soft rough sets for short) which combine interval-valued neutrosophic soft set and rough sets and studied some of its basic properties. This concept is an extension of interval-valued intuitionistic fuzzy soft rough sets (IVIF-soft rough sets).

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Palanikumar, M., Aiyared Iampan, Said Broumi, Lejo J. Manavalan, and K. Sundareswari. "Multi-criteria group decision making method in Pythagorean interval-valued neutrosophic fuzzy soft soft using VIKOR approach." International Journal of Neutrosophic Science 22, no. 1 (2023): 104–13. http://dx.doi.org/10.54216/ijns.220108.

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In contrast to the Pythagorean interval valued fuzzy soft set and the neutrosophic interval valued fuzzy soft set, the Pythagorean neutrosophic interval valued fuzzy soft set is a generalization of these sets. We discuss aggregating PyNIVFS decision matrixes by using aggregated operations. The VIKOR method, which is an extension of neutrosophic fuzzy soft sets, is a powerful method for evaluating multi-criteria group decision making. The score function in this approach is based on the aggregation of the VIKOR method to a PyNIVFSpositive and negative solution. Optimal alternatives are introduce

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Palanikumar, M., Aiyared Iampan, Said Broumi, and G. G.Balaji. "Generalization of neutrosophic interval-valued soft sets with different aggregating operators using multi-criteria group decision-making." International Journal of Neutrosophic Science 22, no. 1 (2023): 114–23. http://dx.doi.org/10.54216/ijns.220109.

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In this paper, we present the Pythagorean neutrosophic interval valued fuzzy soft set. This is a generalization of the Pythagorean interval valued fuzzy soft set as well as the neutrosophic interval valued fuzzy soft set. It is discussed in this paper how an aggregated operation is used to aggregate the decision matrix of PNIVS. There are a number of extensions to the normosophic fuzzy soft sets that involve the use of multi-criteria decisionmaking. The aim of this study is to develop a score function based on aggregating TOPSIS methods in order to find ideal solutions for PNIVS that have both

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Aiyared, Aiyared, G. Manikandan, T. T. Raman, K. Arulmozhi, and Aiyared Iampan. "Type-II q-rung neutrosophic interval valued soft sets." International Journal of Neutrosophic Science 23, no. 3 (2024): 318–28. http://dx.doi.org/10.54216/ijns.230326.

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In this study, the theory of the Type-II q-rung neutrosophic interval valued soft set (Type-II q-rung NIVS) is introduced. We also define a few operations based on the Type-II q-rung NIVS set. Type-II q-rung NIVS sets are formed by extending neutrosophic interval valued soft (NIVS) sets and q-rung fuzzy soft sets. Type-II q-rung NIVS sets and their similarity measures. An illustrative example illustrates how they can be used to successfully address uncertainty-related problems.

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Naveed, Hamza, and Saalam Ali. "Multi-Criteria Decision-Making Approach Based on Correlation Coefficient for Multi-Polar Interval-Valued Neutrosophic Soft Set." Neutrosophic Systems with Applications 24 (December 1, 2024): 18–33. https://doi.org/10.61356/j.nswa.2024.24417.

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The correlation coefficient between two factors is crucial in statistical computation, indicating the extent and evolution of the appropriate link. The precision of applicability evaluations frequently relies on the thoroughness and caliber of data obtained from a certain dataset. Statistical research sometimes entails data marked by intrinsic trade-offs and uncertainty. This study seeks to present m-polar interval-valued neutrosophic soft sets (mPIVNSSs) through the integration of m-polar fuzzy sets with interval-valued neutrosophic soft sets. The suggested mPIVNSS structure is a significantl

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Zulqarnain, Rana Muhammad, Imran Siddique, Aiyared Iampan, and Ebenezer Bonyah. "Algorithms for Multipolar Interval-Valued Neutrosophic Soft Set with Information Measures to Solve Multicriteria Decision-Making Problem." Computational Intelligence and Neuroscience 2021 (November 10, 2021): 1–29. http://dx.doi.org/10.1155/2021/7211399.

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Similarity measures (SM) and correlation coefficients (CC) are used to solve many problems. These problems include vague and imprecise information, excluding the inability to deal with general vagueness and numerous information problems. The main purpose of this research is to propose an m-polar interval-valued neutrosophic soft set (mPIVNSS) by merging the m-polar fuzzy set and interval-valued neutrosophic soft set and then study various operations based on the proposed notion, such as AND operator, OR operator, truth-favorite, and false-favorite operators with their properties. This research

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Al-Sharqi, Faisal Al, Ashraf Al Al-Quran, Noor Kareem Assi Halaf, Mona Aladil, and Maha M. Rasheed. "Algorithm for possibility interval-valued neutrosophic soft decision-making based on distance measures settings." International Journal of Neutrosophic Science 22, no. 3 (2023): 53–68. http://dx.doi.org/10.54216/ijns.220304.

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Soft set(SS) is one of the soft computing techniques that plays an important role in addressing the hiddenness and uncertainty associated with uncertain data. In other hand the idea of interval-valued neutrosophic soft sets (IVNSSs) is a new generalization of the neutrosophic soft sets to the neutrosophic sets when the authors combine the critical features of IVNS and soft sets (SSs) in one model. Accordingly, this model worked to provide decision-makers with more flexibility in the process of interpreting uncertain information. From a scientific point of view, the process of evaluating this h

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Rahman, Atiqe Ur, Muhammad Saeed, Muhammad Arshad, and Salwa El-Morsy. "Multi-Attribute Decision-Support System Based on Aggregations of Interval-Valued Complex Neutrosophic Hypersoft Set." Applied Computational Intelligence and Soft Computing 2021 (December 25, 2021): 1–28. http://dx.doi.org/10.1155/2021/4368770.

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Hypersoft set is an emerging field of study that is meant to address the insufficiency and the limitation of existing soft-set-like models regarding the consideration and the entitlement of multi-argument approximate function. This type of function maps the multi-subparametric tuples to the power set of the universe. It focuses on the partitioning of each attribute into its attribute-valued set that is missing in existing soft-set-like structures. This study aims to introduce novel concepts of complex intuitionistic fuzzy set and complex neutrosophic set under the hypersoft set environment wit

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Palanikumar, M., K. Arulmozhi, Aiyared Iampan, and Said Broumi. "Medical diagnosis decision making using type-II generalized Pythagorean neutrosophic interval valued soft sets." International Journal of Neutrosophic Science 20, no. 1 (2023): 85–105. http://dx.doi.org/10.54216/ijns.200108.

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The theory of type-II generalized Pythagorean neutrosophic interval valued soft set (Type-II PyNSIVS) and its application to real problems are introduced in this study. Additionally, we define a few operations using the type-II PyNSIVS set. The Pythagorean neutrosophic interval valued soft (PyNSIVS) set and Pythagorean fuzzy soft set are both generalized to form the type-II PyNSIVS set. Complement, union, intersection, AND, and OR are some examples of operations that we define. In particular, we demonstrate the applicability of De Morgan’s laws, associative laws, and distributive laws in type-

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Palanikumar, M., Aiyared Iampan, and Said Broumi. "MCGDM based on VIKOR and TOPSIS proposes neutrsophic Fermatean fuzzy soft with aggregation operators." International Journal of Neutrosophic Science 19, no. 3 (2022): 85–94. http://dx.doi.org/10.54216/ijns.190308.

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In this study, we presented a new generalization of the Fermatean interval valued fuzzy soft set (FIVFSS) and the neutrosophic interval valued soft set called the neutrsophic Fermatean interval valued soft set (NSFIVSS). The NSFIVSS decision matrix aggregated operations are the topic of our current discussion. Strong points of view for the generalization of the interval valued fuzzy soft set (IVFSS) known as multi-criteria group decision making (MCGDM) are the TOPSIS and VIKOR techniques. We discuss a score function that combines TOPSIS, VIKOR, and NSFIVSS-positive ideal solution (PIS) and NSF

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Book chapters on the topic "Interval valued fuzzy neutrosophic soft set"

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Palanikumar, M., V. Sreelatha Devi, Chiranjibe Jana, and Gerhard Wilhelm Weber. "Multi-Criteria Group Decision-Making q-Rung Neutrosophic Interval-Valued Soft Set TOPSIS Aggregating Operator for the Selection of Diagnostic Health Imaging." In Fuzzy Optimization, Decision-making and Operations Research. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-35668-1_22.

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Jayasudha, J., and S. Raghavi. "Introduction to Interval-Valued Neutrosophic Hyper-Soft Expert Set." In Springer Proceedings in Mathematics & Statistics. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-1505-6_4.

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Zeng, Wenyi, Hongxing Li, and Shuang Feng. "Some New Entropies on the Interval-Valued Fuzzy Set." In Advances in Intelligent and Soft Computing. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22833-9_22.

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Bin, Chen. "Interval Valued Generalised Fuzzy Soft Expert Set and Its Application." In Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-32456-8_106.

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Ma, Xiuqin, and Norrozila Sulaiman. "An Interval-Valued Fuzzy Soft Set Approach for Normal Parameter Reduction." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-21881-1_34.

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Nan, TaiBen, and HaiDong Zhang. "Reverse Triple I Reasoning Method Based on Interval-Valued Fuzzy Soft Set." In Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-70665-4_172.

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Ali, Iftikhar, Aftab Ahmed Khan, Salman Qureshi, Mudassar Umar, Dagmar Haase, and Ihab Hijazi. "A Hybrid Approach Integrating 3D City Models, Remotely Sensed SAR Data and Interval-Valued Fuzzy Soft Set Based Decision Making for Post Disaster Mapping of Urban Areas." In Lecture Notes in Geoinformation and Cartography. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-12181-9_6.

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R., Subha,, and Mohana K. "IMPROVED CORRELATION COEFFICIENTS OF FERMATEAN PENTAPARTITIONED SINGLE VALUED NEUTROSOPHIC SETS AND INTERVAL FERMATEAN PENTAPARTITIONED NEUTROSOPHIC SETS FOR MULTIPLE ATTRIBUTE DECISION MAKING." In Recent Trends in Fuzzy Set Theory and its Applications. Iterative International Publishers, Selfypage Developers Pvt Ltd, 2024. http://dx.doi.org/10.58532/nbennurch282.

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A correlation coefficient is a statistical measure that helps identify how many changes in one value signal change in another. Wang's single valued neutrosophic sets were improvised into Fermatean Pentapartitioned single valued neutrosophic sets. We investigated the attributes of the interval Fermatean pentapartitioned neutrosophic sets and Fermatean pentapartitioned single-valued neutrosophic sets. Additionally, we have used this idea in many decisionmaking techniques using interval and Fermatean pentapartitioned single valued neutrosophic environments. Eventually we presuming (that) an examp

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Acharjya, D. P., and Dhruv Arya. "Multicriteria Decision-Making Using Interval Valued Neutrosophic Soft Set." In Artificial Intelligence and Global Society. Chapman and Hall/CRC, 2021. http://dx.doi.org/10.1201/9781003006602-8.

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Ali, Mumtaz, Florentin Smarandache, and Luige Vladareanu. "Neutrosophic Sets and Logic." In Emerging Research on Applied Fuzzy Sets and Intuitionistic Fuzzy Matrices. IGI Global, 2017. http://dx.doi.org/10.4018/978-1-5225-0914-1.ch002.

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Neutrosophic sets and Logic plays a significant role in approximation theory. It is a generalization of fuzzy sets and intuitionistic fuzzy set. Neutrosophic set is based on the neutrosophic philosophy in which every idea Z, has opposite denoted as anti(Z) and its neutral which is denoted as neut(Z). This is the main feature of neutrosophic sets and logic. This chapter is about the basic concepts of neutrosophic sets as well as some of their hybrid structures. This chapter starts with the introduction of fuzzy sets and intuitionistic fuzzy sets respectively. The notions of neutrosophic set are

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Conference papers on the topic "Interval valued fuzzy neutrosophic soft set"

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Alkhazaleh, Shawkat. "n-valued refined neutrosophic soft set theory." In 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2016. http://dx.doi.org/10.1109/fuzz-ieee.2016.7738004.

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Liu, Yaya, and Keyun Qin. "Entropy on Interval-Valued Intuitionistic Fuzzy Soft Set." In 2015 IEEE International Conferences on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; and Pervasive Intelligence and Computing (CIT/IUCC/DASC/PICOM). IEEE, 2015. http://dx.doi.org/10.1109/cit/iucc/dasc/picom.2015.202.

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Shanthi, S. Anita, and M. Gayathri. "Entropy measure on interval valued picture fuzzy soft set." In PHYSICAL MESOMECHANICS OF CONDENSED MATTER: Physical Principles of Multiscale Structure Formation and the Mechanisms of Nonlinear Behavior: MESO2022. AIP Publishing, 2023. http://dx.doi.org/10.1063/5.0144193.

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Xue, Binbin, Lu Wang, and Keyun Qin. "An interval-valued fuzzy soft set based triple I method." In 2017 12th International Conference on Intelligent Systems and Knowledge Engineering (ISKE). IEEE, 2017. http://dx.doi.org/10.1109/iske.2017.8258816.

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Zhang, Lishi. "A Novel Decision Making Based on Interval Valued Intuitionistic Fuzzy Soft Set." In 2014 International Conference on Mechatronics, Electronic, Industrial and Control Engineering. Atlantis Press, 2014. http://dx.doi.org/10.2991/meic-14.2014.342.

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Mukherjee, Anjan, and Ajoy Kanti Das. "Application of Interval Valued Intuitionistic Fuzzy Soft Set in Investment Decision Making." In 2015 Fifth International Conference on Advances in Computing & Communications (ICACC). IEEE, 2015. http://dx.doi.org/10.1109/icacc.2015.37.

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Wenhua, Jia, Kong Zhi, Wang Liqian, and Wang Lifu. "Sequence interval-valued fuzzy soft set and its application in decision making." In 2016 Chinese Control and Decision Conference (CCDC). IEEE, 2016. http://dx.doi.org/10.1109/ccdc.2016.7531513.

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Mukherjee, Anjan, and Ajoy Kanti Das. "Interval valued intuitionistic fuzzy soft multi set theoretic approach to decision making problems." In 2015 International Conference on Computer, Communication and Control (IC4). IEEE, 2015. http://dx.doi.org/10.1109/ic4.2015.7375640.

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Tripathy, B. K., and Abhilash Panigrahi. "Interval-valued intuitionistic fuzzy parameterized soft set theory and its application in decision-making." In 2016 10th International Conference on Intelligent Systems and Control (ISCO). IEEE, 2016. http://dx.doi.org/10.1109/isco.2016.7726952.

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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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