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Relevant bibliographies by topics / Neutrosophic Soft Set (NSS)

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Academic literature on the topic 'Neutrosophic Soft Set (NSS)'

Author: Grafiati

Published: 4 June 2025

Last updated: 23 June 2025

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Journal articles on the topic "Neutrosophic Soft Set (NSS)"

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Tasbozan, Hatice. "Near neutrosophic soft set." AIMS Mathematics 9, no. 4 (2024): 9447–54. http://dx.doi.org/10.3934/math.2024461.

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<abstract><p>In this article, the notion of near neutrosophic soft sets $ (Nss) $ is obtained by combining the notion of $ Nss $ and the notion of near approximation space. Accordingly, a new set was obtained by restricting the set of features with the help of the indiffirentiable relation defined on the set. The features and definitions that the set will provide are given, and, based on these features, the benefits that will be provided when they are implemented are investigated in the example.</p></abstract>

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Bhargavi, K., and B. Sathish Babu. "Uncertainty Aware Resource Provisioning Framework for Cloud Using Expected 3-SARSA Learning Agent: NSS and FNSS Based Approach." Cybernetics and Information Technologies 19, no. 3 (2019): 94–117. http://dx.doi.org/10.2478/cait-2019-0028.

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Abstract Efficiently provisioning the resources in a large computing domain like cloud is challenging due to uncertainty in resource demands and computation ability of the cloud resources. Inefficient provisioning of the resources leads to several issues in terms of the drop in Quality of Service (QoS), violation of Service Level Agreement (SLA), over-provisioning of resources, under-provisioning of resources and so on. The main objective of the paper is to formulate optimal resource provisioning policies by efficiently handling the uncertainties in the jobs and resources with the application of Neutrosophic Soft-Set (NSS) and Fuzzy Neutrosophic Soft-Set (FNSS). The performance of the proposed work compared to the existing fuzzy auto scaling work achieves the throughput of 80% with the learning rate of 75% on homogeneous and heterogeneous workloads by considering the RUBiS, RUBBoS, and Olio benchmark applications.

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Ebtesam, Ebtesam, and Ebtesam Al Al-Mansor. "Leveraging Bat Algorithm with Rough Neutrosophic Soft Set for Enhanced Oral Cancer Detection and Classification." International Journal of Neutrosophic Science 24, no. 4 (2024): 71–81. http://dx.doi.org/10.54216/ijns.240405.

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Neutrosophic soft sets (NSS) are highly effective in representing neutral uncertain data. NSS model attracts several authors because it has huge range of applications in several areas such as decision-making, data analysis, smoothness of functions, probability theory, measurement theory, predicting, and operations research. Oral squamous cell carcinoma (OSCC) is the most general tumor around the world and its occurrence is on the increase in several populations. Early diagnosis plays vital role in improving diagnosis, treatment outcomes and survival rates. Although the new developments in understanding molecular mechanisms, late analysis and the implementation of precision medicine for OSCC patients continue to present problems. Early diagnosis and detection can support doctors in offering optimum patient care and effectual treatment. In recent years, the execution of several machine-learning (ML) approaches in cancer analysis has provided valuable insights, facilitating more effective and precise treatment decision-making. Oral Cancer screening can progress with the execution of artificial intelligence (AI) approaches. AI offers support to the oncology region by correctly examining a huge database in many imaging modalities. This article develops a Bat Algorithm with Rough Neutrosophic Soft Set for Oral Cancer Diagnosis (BARNSS-OCD) technique. The main intention of the BARNSS-OCD technique is to exploit deep learning (DL) model for enhanced identification of OC. In the BARNSS-OCD technique, median filtering (MF) is used for image pre-processing and the feature extraction takes place using deep convolutional neural network (DCNN) model. In addition, bat algorithm (BA) is used for the hyperparameter selection of the DCNN model. For OC detection process, the BARNSS-OCD technique applies RNSS model. To exhibit the improved performance of the BARNSS-OCD technique, a sequence of experiments is involved. The simulation outcomes indicate that the BARNSS-OCD technique gains better performance compared to other DL models

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Yousef, Yousef, Yousef Al Al-Qudah, Abdulqader O. Hamadameen, et al. "Matrices and Correlation Coefficient for possibility interval-valued neutrosophic hypersoft sets and their applications in real-life." International Journal of Neutrosophic Science 26, no. 1 (2025): 254–65. https://doi.org/10.54216/ijns.260122.

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In this careful study , through the concept possibility interval valued neutrosophic hyper soft set (abbreviated as piv-NHSS) which is combined from the hypersoft set (HSS) and Interval-valued neutrosophic set under the posobolity degree and each iv-NHSS is assigned a possibility degree in the interval [0, 1]. Based on this concept, we present a more flexible, expanded method for a previous concept named possibility interval valued neutrosophic hyper soft matrix (piv-NHSM) as a new generalization of piv-NHSS. In this work, we also present nseveral algebraic operations and also all the mathematical properties associated with this model. In addition to the above, we have presented a clear algorithm based on the matrix properties of this model, which has been used to solve one of the multi-property decision-making problems. Finally, the correlation coefficient for this concept was defined and explained in detail according to an approved mechanism, with a numerical example provided to illustrate the mechanism of use. Moreover, we develop a new algorithm for solving the decision-making issue based on the proposed correlation coefficient for piv-NHSS .

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Jayasudha, J., and S. Raghavi. "Futher Operations on Neutrosophic Hypersoft Matrices and Application in Decision Making." HyperSoft Set Methods in Engineering 2 (October 28, 2024): 119–35. http://dx.doi.org/10.61356/j.hsse.2024.2403.

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The main objective of this paper is to extend the concept of Neutrosophic Hypersoft Matrix theory. Neutrosophic soft matrix parametrically evaluates the attributes chosen whereas Neutrosophic hypersoft matrix can parametrically evaluate the sub-attributes of the attributes chosen. Some notions and operations related to Neutrosophic Hypersoft matrices (NHSMs) such as Row-NHSM, Column-NHSM, Diagonal-NHSM, Proper-NHS submatrix, Disjoint NHSM, Extended union (NHSM), Extended intersection (NHSM), addition, subtraction, AND-product and OR-product on NHSM have been introduced with examples. Further a new NHSM-algorithm has been developed based on value matrix, grace matrix and mean matrix to solve Neutrosophic Hypersoft Set based decision-making problems.

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Zulqarnain, Rana Muhammad, Imran Siddique, Rifaqat Ali, Fahd Jarad, Abdul Samad, and Thabet Abdeljawad. "Neutrosophic Hypersoft Matrices with Application to Solve Multiattributive Decision-Making Problems." Complexity 2021 (June 4, 2021): 1–17. http://dx.doi.org/10.1155/2021/5589874.

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The concept of the neutrosophic hypersoft set (NHSS) is a parameterized family that deals with the subattributes of the parameters and is a proper extension of the neutrosophic soft set to accurately assess the deficiencies, anxiety, and uncertainty in decision-making. Compared with existing research, NHSS can accommodate more uncertainty, which is the most significant technique for describing fuzzy information in the decision-making process. The main objective of the follow-up study is to develop the theory of neutrosophic hypersoft matrix (NHSM). The NHSM is the generalized form of a neutrosophic soft matrix (NSM). Some fundamental operations and score function for NHSMs have been introduced with their desirable properties. Furthermore, we introduce the logical operators such as OR-operator and AND-operator with their fundamental properties in the following research. The necessity and possibility operations for NHSMs have been established. Utilizing the developed score function, a decision-making methodology has been developed to solve the multiattribute decision-making (MADM) problem. To ensure the validity of the proposed approach, a numerical illustration has been described for the selection of competent faculty member. The practicality and effectiveness of the current approach are proved through comparative analysis with the assistance of some existing studies.

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Zulqarnain, Rana Muhammad, Wen Xiu Ma, Imran Siddique, Shahid Hussain Gurmani, Fahd Jarad, and Muhammad Irfan Ahamad. "Extension of aggregation operators to site selection for solid waste management under neutrosophic hypersoft set." AIMS Mathematics 8, no. 2 (2023): 4168–201. http://dx.doi.org/10.3934/math.2023208.

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<abstract> <p>With the fast growth of the economy and rapid urbanization, the waste produced by the urban population also rises as the population increases. Due to communal, ecological, and financial constrictions, indicating a landfill site has become perplexing. Also, the choice of the landfill site is oppressed with vagueness and complexity due to the deficiency of information from experts and the existence of indeterminate data in the decision-making (DM) process. The neutrosophic hypersoft set (NHSS) is the most generalized form of the neutrosophic soft set, which deals with the multi-sub-attributes of the alternatives. The NHSS accurately judges the insufficiencies, concerns, and hesitation in the DM process compared to IFHSS and PFHSS, considering the truthiness, falsity, and indeterminacy of each sub-attribute of given parameters. This research extant the operational laws for neutrosophic hypersoft numbers (NHSNs). Furthermore, we introduce the aggregation operators (AOs) for NHSS, such as neutrosophic hypersoft weighted average (NHSWA) and neutrosophic hypersoft weighted geometric (NHSWG) operators, with their necessary properties. Also, a novel multi-criteria decision-making (MCDM) approach has been developed for site selection of solid waste management (SWM). Moreover, a numerical description is presented to confirm the reliability and usability of the proposed technique. The output of the advocated algorithm is compared with the related models already established to regulate the favorable features of the planned study.</p> </abstract>

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Peng, Xindong, and Florentin Smarandache. "A decision-making framework for China’s rare earth industry security evaluation by neutrosophic soft CoCoSo method." Journal of Intelligent & Fuzzy Systems 39, no. 5 (2020): 7571–85. http://dx.doi.org/10.3233/jifs-200847.

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The rare earth industry is a crucial strategic industry that is related to the national economy and national security. In the context of economic globalization, international competition is becoming increasingly fierce, and the rare earth industry is facing a more severe survival and development environment than ever before. Although China is the greatest world’s rare earth country in rare earth reserves, production, consumption and export volume, it is not a rare earth power. The rare earth industry has no right to speak in the international market. The comparative advantage is weakening and the security of rare earth industry appears. Therefore, studying the rare earth industry security has important theoretical and practical significance. When measuring the China’s rare earth industry security, the primary problem involves tremendous uncertainty. Neutrosophic soft set (NSS), depicted by the parameterized form of truth membership, falsity membership and indeterminacy membership, is a more serviceable pattern for capturing uncertainty. In this paper, five dimensions of rare earth industry security are identified and then prioritized against twelve different criteria relevant to structure, organization, layout, policy and ecological aspects of industry security. Then, the objective weight is computed by CRITIC (Criteria Importance Through Inter-criteria Correlation) method while the integrated weight is determined by concurrently revealing subjective weight and objective weight. Later, neutrosophic soft decision making method based CoCoSo (Combined Compromise Solution) is explored for settling the issue of low discrimination. Lastly, the feasibility and validity of the developed algorithm is verified by the issue of China’s rare earth industry security evaluation.

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Hashmi, Masooma Raza, Syeda Tayyba Tehrim, Muhammad Riaz, Dragan Pamucar, and Goran Cirovic. "Spherical Linear Diophantine Fuzzy Soft Rough Sets with Multi-Criteria Decision Making." Axioms 10, no. 3 (2021): 185. http://dx.doi.org/10.3390/axioms10030185.

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Modeling uncertainties with spherical linear Diophantine fuzzy sets (SLDFSs) is a robust approach towards engineering, information management, medicine, multi-criteria decision-making (MCDM) applications. The existing concepts of neutrosophic sets (NSs), picture fuzzy sets (PFSs), and spherical fuzzy sets (SFSs) are strong models for MCDM. Nevertheless, these models have certain limitations for three indexes, satisfaction (membership), dissatisfaction (non-membership), refusal/abstain (indeterminacy) grades. A SLDFS with the use of reference parameters becomes an advanced approach to deal with uncertainties in MCDM and to remove strict limitations of above grades. In this approach the decision makers (DMs) have the freedom for the selection of above three indexes in [0,1]. The addition of reference parameters with three index/grades is a more effective approach to analyze DMs opinion. We discuss the concept of spherical linear Diophantine fuzzy numbers (SLDFNs) and certain properties of SLDFSs and SLDFNs. These concepts are illustrated by examples and graphical representation. Some score functions for comparison of LDFNs are developed. We introduce the novel concepts of spherical linear Diophantine fuzzy soft rough set (SLDFSRS) and spherical linear Diophantine fuzzy soft approximation space. The proposed model of SLDFSRS is a robust hybrid model of SLDFS, soft set, and rough set. We develop new algorithms for MCDM of suitable clean energy technology. We use the concepts of score functions, reduct, and core for the optimal decision. A brief comparative analysis of the proposed approach with some existing techniques is established to indicate the validity, flexibility, and superiority of the suggested MCDM approach.

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Mesfer, Mesfer. "Blockchain with Single-Valued Neutrosophic Hypersoft Sets Assisted Threat Detection for Secure IoT Assisted Consumer Electronics." International Journal of Neutrosophic Science 25, no. 1 (2025): 160–71. http://dx.doi.org/10.54216/ijns.250114.

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The breakthrough technologies of the Internet of Things (IoT) have modernized classical Consumer Electronics (CE) into next-generation CE with high intelligence and connectivity. This connectivity amongst appliances, actuators, sensors, etc., offers automated control in CE and enables better data availability. However, the data traffic has been exponentially increased owing to its decentralization, diversity, and increasing number of CE devices. Furthermore, the static network-based approaches need exclusive management and manual configuration of CE devices. The generalization of a Neutrosophic Hypersoft Set (NHSS) is a concept of a soft set. This architecture is a mixture of neutrosophic sets with hypersoft sets. Therefore, the study introduce a Blockchain with Single-Valued Neutrosophic Hypersoft Sets Assisted Threat Detection (BCSVNHS-TD) technique for Secure IoT Assisted CE. The presented BCSVNHS-TD technique applies BC technology for secure communication among CEs. For threat detection, the BCSVNHS-TD method introduces the SVNHS model. Also, the parameter selection of the SVNHS method takes place using the chicken swarm optimization (CSO) technique. An extensive set of tests was involved for exhibiting the better effiency of the BCSVNHS-TD method. The experimental results emphasized that the BCSVNHS-TD method reaches optimal results over other techniques

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Book chapters on the topic "Neutrosophic Soft Set (NSS)"

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Smarandache, Florentin. "Introduction to Neutrosophy, Neutrosophic Set, Neutrosophic Probability, Neutrosophic Statistics and Their Applications to Decision Making." In Studies in Fuzziness and Soft Computing. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-78505-4_1.

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Aini, Qonita Qurratu, Imam Mukhlash, Kistosil Fahim, Jasmir, and Fatia Fatimah. "Neutrosophic Soft Set for Forecasting Indonesian Bond Yields." In Lecture Notes in Networks and Systems. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-67192-0_77.

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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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Anitha, S., and A. Francina Shalini. "Entropy and Distance Measures of Bipolar Pythagorean Neutrosophic Soft Set." In Engineering, Science, and Sustainability. CRC Press, 2023. http://dx.doi.org/10.4324/9781003388982-37.

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Subashini, P., and R. Sophia Porchelvi. "On Solving a Multi-criteria Decision Making Problem Using Neutrosophic Soft Set and Its Application." In Lecture Notes in Networks and Systems. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-0185-1_4.

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Naz, Sumera, Syeda Saba Fatima, Shariq Aziz Butt, Mehwish Majeed, and Areej Fatima. "A Novel MAGDM Approach for Software Quality Assessment: A Focus on Microsoft DevOps Transformation Using 2-Tuple Linguistic Single-Valued Neutrosophic Set." In Studies in Fuzziness and Soft Computing. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-78505-4_21.

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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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Debnath, Somen. "Neutrosophic Fuzzy Soft Matrix Theory and Its Application in Group Decision Making." In Handbook of Research on Advances and Applications of Fuzzy Sets and Logic. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-7998-7979-4.ch033.

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In 2020, Sujit et al. introduced the notion of the neutrosophic fuzzy set (NFS) to deal with uncertainty under a fuzzy environment where the fuzzy membership grade of every element of the field of the domain is associated with three independent neutrosophic components, namely truth, indeterminacy, and falsity membership grade. The main focus of the chapter is to introduce a neutrosophic fuzzy soft set (NFSS) to deal with uncertainty parametrically, and it gives the approximate solution to the problem. NFSS is a mixture of a neutrosophic set, fuzzy sets, and soft sets. So, it can be treated as a hybrid structure that gives more flexibility to solve multi-criteria decision-making problems under a fuzzy environment. NFSS evolved as an extension of fuzzy set, soft set, neutrosophic set, etc. Then the authors propose an algorithmic approach for group decision-making (GDM) problems using a neutrosophic fuzzy soft matrix (NFSM) and its related properties. Finally, an illustrative example shows the applicability of the proposed approach.

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Mahapatra, Biplab Sinha, Mihir Baran Bera, Manoj Kumar Mondal, and Pinaki Pratim Acharjya. "A Probabilistic Approach for Renewable Energy Alternative Selection Through Correlation-Based Neutrosophic TOPSIS Approach." In Advances in Chemical and Materials Engineering. IGI Global, 2024. https://doi.org/10.4018/979-8-3693-3204-7.ch012.

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The selection of renewable energy alternatives becomes critical due to several quantitative and qualitative factors describing the criteria. Often these criteria cannot be appropriately quantified due to linguistic assessment. Hence, selecting renewable energy alternatives becomes a complex, uncertain multi-criteria decision-making (MCDM) problem. Several soft set-based TOPSIS approaches are used to solve uncertain MCDM problems. In this chapter, the authors introduce a neutrosophic soft set-based TOPSIS approach to solve MCDM problems in an uncertain situation. The TOPSIS methods calculate the relative measure of distance between its positive ideal solution (PIS) and negative ideal solution (NIS). This distance is often measured by Euclidean or Hamming techniques which create ambiguity and computational complexities. The authors introduce a correlation-based TOPSIS approach to solve an MCDM problem to avoid this ambiguity and computational hazards. A numerical discussion of renewable energy alternative selection is given to establish the proposed approach.

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Sinha, Kalyan, and Pinaki Majumdar. "Neutrosophic Soft Digraph." In Advances in Data Mining and Database Management. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-1313-2.ch012.

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Neutrosophic soft sets are an important tool to deal with the uncertainty-based real and scientific problems. In this chapter, the idea of neutrosophic soft (NS) digraph has been developed. These digraphs are mainly the graphical representation of neutrosophic soft sets. A graphical study of various set theoretic operations such as union, intersection, complement, cross product, etc. are shown here. Also, some properties of NS digraphs along with theoretical concepts are shown here. In the last part of the chapter, a decision-making problem has been solved with the help of NS digraphs. Also, an algorithm is provided to solve the decision-making problems using NS digraph. Finally, a comparative study with proposed future work along this direction has been provided.

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Conference papers on the topic "Neutrosophic Soft Set (NSS)"

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Al-Hijjawi, Sumyyah, Abd Ghafur Ahmad, and Shawkat Alkhazaleh. "Effective neutrosophic soft expert set (ENSES)." In 5TH INTERNATIONAL CONFERENCE ON MATHEMATICAL SCIENCES (ICMS5). AIP Publishing, 2024. http://dx.doi.org/10.1063/5.0228107.

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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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Arockiarani, I. "A fuzzy neutrosophic soft set model in medical diagnosis." In 2014 IEEE Conference on Norbert Wiener in the 21st Century (21CW). IEEE, 2014. http://dx.doi.org/10.1109/norbert.2014.6893943.

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Hassan, Nasruddin, and Ashraf Al-Quran. "Possibility neutrosophic vague soft expert set for decision under uncertainty." In THE 4TH INTERNATIONAL CONFERENCE ON MATHEMATICAL SCIENCES: Mathematical Sciences: Championing the Way in a Problem Based and Data Driven Society. Author(s), 2017. http://dx.doi.org/10.1063/1.4980956.

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Binu, R., and P. Isaac. "Weighted Similarity Measure and Decision Making in Clinical Application of Neutrosophic Soft Set." In 2019 International Conference on Data Science and Engineering (ICDSE). IEEE, 2019. http://dx.doi.org/10.1109/icdse47409.2019.8971797.

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