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Relevant bibliographies by topics / Weighted neutrosophic soft sets

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Academic literature on the topic 'Weighted neutrosophic soft sets'

Author: Grafiati

Published: 2 June 2025

Last updated: 31 July 2025

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Journal articles on the topic "Weighted neutrosophic soft sets"

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Jayaprakash, Poornima, and Sandhiya Sundar. "Neutrosophic soft set matrix and their applications based on multi criteria decision-making problems." Multidisciplinary Science Journal 6 (December 15, 2023): 2024ss0110. http://dx.doi.org/10.31893/multiscience.2024ss0110.

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Importance of decision-making problems in uncertain environments cannot be overstated. Soft set theory and neutrosophic soft set theory are advanced mathematical techniques that have recently been developed to better handle these uncertain, incomplete, and inconsistent data sets. The concepts of neutrosophic soft set, neutrosophic soft matrix, and its operations are presented in this work. To compare the neutrosophic soft sets, we also provide score, certainty, and accuracy functions. Afterward, we create the neutrosophic arithmetic operator (NA), neutrosophic weighted arithmetic operator neut

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Dong, Hou, and Gong. "Algorithm for Neutrosophic Soft Sets in Stochastic Multi-Criteria Group Decision Making Based on Prospect Theory." Symmetry 11, no. 9 (2019): 1085. http://dx.doi.org/10.3390/sym11091085.

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To address issues involving inconsistencies, this paper proposes a stochastic multi-criteria group decision making algorithm based on neutrosophic soft sets, which includes a pair of asymmetric functions: Truth-membership and false-membership, and an indeterminacy-membership function. For integrating an inherent stochastic, the algorithm expresses the weights of decision makers and parameter subjective weights by neutrosophic numbers instead of determinate values. Additionally, the algorithm is guided by the prospect theory, which incorporates psychological expectations of decision makers into

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Zhang, Fu, and Weimin Ma. "Study on Chaotic Multi-Attribute Group Decision Making Based on Weighted Neutrosophic Fuzzy Soft Rough Sets." Mathematics 11, no. 4 (2023): 1034. http://dx.doi.org/10.3390/math11041034.

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In this article, we have proposed a multi-attribute group decision making (MAGDM) with a new scenario or new condition named Chaotic MAGDM, in which not only the weights of the decision makers (DMs) and the weights of the decision attributes are considered, but also the familiarity of the DMs with the attributes are considered. Then we applied the weighted neutrosophic fuzzy soft rough set theory to Chaotic MAGDM and proposed a new algorithm for MAGDM. Moreover, we provide a case study to demonstrate the application of the algorithm. Our contributions to the literature are as follows: (1) fami

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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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Surapati, Pramanik* Shyamal Dalapati. "GRA BASED MULTI CRITERIA DECISION MAKING IN GENERALIZED NEUTROSOPHIC SOFT SET ENVIRONMENT." Global Journal of Engineering Science and Research Management 3, no. 5 (2016): 153–69. https://doi.org/10.5281/zenodo.53753.

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The main objective of the paper is to propose generalized neutrosophic soft multi criteria decision making based on grey relational analysis. The concept of generalized neutrosophic soft sets has been derived from the hybridization of the concepts of neutrosophic set and soft set. In this paper we have defined neutrosophic soft weighted average operator in order to aggregate the individual decision maker’s opinion into a common opinion based on choice parameters of the evaluators. In the decision making process, the decision makers provide the rating of alternatives with respect to the p

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Althuniyan, Najla, Abedallah Al-shboul, Sarah Aljohani, et al. "Decision-Making with Fermatean Neutrosophic Vague Soft Sets Using a Technique for Order of Preference by Similarity to Ideal Solution." Axioms 14, no. 5 (2025): 381. https://doi.org/10.3390/axioms14050381.

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This study addresses the challenge of effectively modeling uncertainty and hesitation in complex decision-making environments, where traditional fuzzy and vague set models often fall short. To overcome these limitations, we propose the Fermatean neutrosophic vague soft set (FNVSS), an advanced extension that integrates the concepts of neutrosophic sets with Fermatean membership functions into the framework of vague sets. The FNVSS model enhances the representation of truth, indeterminacy, and falsity degrees, providing greater flexibility and resilience in capturing ambiguous and imprecise inf

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Nasser, Nasser. "Automated Learning Style Prediction using Weighted Neutrosophic Fuzzy Soft Rough Sets in E-learning Platform." International Journal of Neutrosophic Science 25, no. 1 (2025): 104–16. http://dx.doi.org/10.54216/ijns.250109.

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Neutrosophic fuzzy logic (NFL) is a prolongation of classical FL that integrates the neutrosophic conception that handles the indeterminacy concept. This method offers a more comprehensive and flexible architecture to handle inconsistent, uncertain, and indeterminate data, which makes it especially helpful in complicated reasoning and decision-making scenarios where classical FL might be defeated. A learning scheme, which is made from the internet and computer as the main components, is called as an e-learning platform. Although the training might happen on or off campuses, utilizing the inter

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Smarandache, Florentin, Mona Mohamed, and Michael Voskoglou. "Evaluating Blockchain Cybersecurity Based on Tree Soft and Opinion Weight Criteria Method under Uncertainty Climate." HyperSoft Set Methods in Engineering 1 (January 3, 2024): 1–10. http://dx.doi.org/10.61356/j.hsse.2024.17850.

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In the era of digital transformation (DT), many digital technologies have emerged and have had a positive impact on society. Nevertheless, because of certain issues with existing technologies, innovative technology has developed to eradicate them. Fog computing (FC) plays a vital role as an intermediate between edge layer and cloud computing (CC) to resolve limited resources and capabilities. In the same vein, blockchain technology (BCT) is responsible for resolving privacy and security issues that IoT suffers from. Due to using cryptography rules and hashing which is utilized in BCT to preven

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Mohamed, Mona, and Alaa Salem. "Holistic Methodology of Hypersoft in Tandem with Uncertainty-based Triangular Neutrosophic for Wave Energy Converter Optimization." Multicriteria Algorithms with Applications 5 (October 1, 2024): 18–31. http://dx.doi.org/10.61356/j.mawa.2024.5395.

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Global warming, environmental degradation, and climate change have recently emerged as compelling arguments against the combustion of fossil fuels. As well Eliminating and forgoing the intake of fossil fuels is also encouraged by the Sustainable Development Agenda's goals. The healthy substitute for fossil fuels, renewable energy is one of the main devoid power sources found in our natural surroundings. An effective proposition for harnessing wave energy with an emphasis on increasing energy and efficiency are wave energy converters, or WEnCos. It contributes to producing a clean, limitless en

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Gulistan, Muhammad, Mutaz Mohammad, Faruk Karaaslan, Seifedine Kadry, Salma Khan, and Hafiz Abdul Wahab. "Neutrosophic cubic Heronian mean operators with applications in multiple attribute group decision-making using cosine similarity functions." International Journal of Distributed Sensor Networks 15, no. 9 (2019): 155014771987761. http://dx.doi.org/10.1177/1550147719877613.

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This article introduces the concept of Heronian mean operators, geometric Heronian mean operators, neutrosophic cubic number–improved generalized weighted Heronian mean operators, neutrosophic cubic number–improved generalized weighted geometric Heronian mean operators. These operators actually generalize the operators of fuzzy sets, cubic sets, and neutrosophic sets. We investigate the average weighted operator on neutrosophic cubic sets and weighted geometric operator on neutrosophic cubic sets to aggregate the neutrosophic cubic information. After this, based on average weighted and geometr

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Book chapters on the topic "Weighted neutrosophic soft sets"

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Maji, Pabitra Kumar. "An Application of Weighted Neutrosophic Soft Sets in a Decision-Making Problem." In Springer Proceedings in Mathematics & Statistics. Springer India, 2015. http://dx.doi.org/10.1007/978-81-322-2301-6_16.

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Mukherjee, Anjan. "Interval-Valued Neutrosophic Soft Sets." In Generalized Rough Sets. Springer India, 2015. http://dx.doi.org/10.1007/978-81-322-2458-7_7.

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Kostelić, Katarina, and Marli Gonan Božac. "Nuances of Satisfaction: An Approach Using Neutrosophic Sets." In Studies in Fuzziness and Soft Computing. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-78505-4_19.

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Syropoulos, Apostolos, Binod Kumar Sharma, and Basil K. Papadopoulos. "Neutrosophic Sets and the Production and Distribution of Electricity." In Studies in Fuzziness and Soft Computing. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-78505-4_20.

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Boltürk, Eda, Ali Karaşan, and Cengiz Kahraman. "Simple Additive Weighting and Weighted Product Methods Using Neutrosophic Sets." In Fuzzy Multi-criteria Decision-Making Using Neutrosophic Sets. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-00045-5_25.

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Radha, R., M. Kishorekumar, S. Krishnaprakash, Said Broumi, and S. A. Edalatpanah. "Pentapartitioned Neutrosophic Weighted Geometric Bonferroni Mean Operators in MultipleAttribute Decision Making." In Data-Driven Modelling with Fuzzy Sets. CRC Press, 2024. http://dx.doi.org/10.1201/9781003487104-9.

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Bharatraj, Janani, and M. Clement Joe Anand. "Power Harmonic Weighted Aggregation Operator on Single-Valued Trapezoidal Neutrosophic Numbers and Interval-Valued Neutrosophic Sets." In Fuzzy Multi-criteria Decision-Making Using Neutrosophic Sets. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-00045-5_3.

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Narmada Devi, R., Kala Raja Mohan, Nagadevi Bala Nagaram, Sathish Kumar Kumaravel, and Regan Murugesan. "Promothee Method in Selecting Best Smart Phone Supplier by Fertamean Neutrosophic Sets." In Studies in Fuzziness and Soft Computing. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-78505-4_18.

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Ajay, Devaraj, and P. Chellamani. "Pythagorean Neutrosophic Soft Sets and Their Application to Decision-Making Scenario." In Intelligent and Fuzzy Techniques for Emerging Conditions and Digital Transformation. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-85577-2_65.

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Xu, Xin-Hong, De-Chao Li, and Zhi-Song Liu. "Weighted Interval-Valued Belief Structures on Atanassov’s Intuitionistic Fuzzy Sets." In Quantitative Logic and Soft Computing 2016. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-46206-6_50.

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Conference papers on the topic "Weighted neutrosophic soft sets"

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Kaur, Kamalpreet, and Asha Gupta. "q-rung orthopair neutrosophic fuzzy rough sets with an application based on multi-criteria decision-making." In 2024 11th International Conference on Soft Computing & Machine Intelligence (ISCMI). IEEE, 2024. https://doi.org/10.1109/iscmi63661.2024.10851579.

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Al-Quran, Ashraf, and Nasruddin Hassan. "Mapping on complex neutrosophic soft expert sets." In THE 2017 UKM FST POSTGRADUATE COLLOQUIUM: Proceedings of the University Kebangsaan Malaysia, Faculty of Science and Technology 2017 Postgraduate Colloquium. Author(s), 2018. http://dx.doi.org/10.1063/1.5028026.

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Jeeva, D., A. Vadivel, and D. Sivakumar. "M-open sets in neutrosophic soft topological spaces." In THE 12TH INTERNATIONAL CONFERENCE ON MECHANICAL ENGINEERING (TSME-ICoME 2022). AIP Publishing, 2024. http://dx.doi.org/10.1063/5.0208371.

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Deli, Irfan, Yusuf Subas, Florentin Smarandache, and Mumtaz Ali. "Interval valued bipolar fuzzy weighted neutrosophic sets and their application." In 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2016. http://dx.doi.org/10.1109/fuzz-ieee.2016.7738002.

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Mathews, Priya, and Lovelymol Sebastian. "Hausdorff distance of neutrosophic fuzzy sets for medical diagnosis." In 2nd INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCES-MODELLING, COMPUTING AND SOFT COMPUTING (CSMCS 2022). AIP Publishing, 2023. http://dx.doi.org/10.1063/5.0154022.

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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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Li, Xuelong, Jian Yang, and Qi Wang. "Nonrigid Points Alignment with Soft-weighted Selection." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/111.

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Point set registration (PSR) is a crucial problem in computer vision and pattern recognition. Existing PSR methods cannot align point sets robustly due to degradations, such as deformation, noise, occlusion, outlier, and multi-view changes. In this paper, we present a self-selected regularized Gaussian fields criterion for nonrigid point matching. Unlike most existing methods, we formulate the registration problem as a sparse approximation task with low rank constraint in reproducing kernel Hilbert space (RKHS). A self-selected mechanism is used to dynamically assign real-valued label for each

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Chiao, Kuo-Ping. "Interval type 2 fuzzy sets multiple criteria decision making based on quantifier guided aggregation ordered weighted averaging operator." In 2017 Joint 17th World Congress of International Fuzzy Systems Association and 9th International Conference on Soft Computing and Intelligent Systems (IFSA-SCIS). IEEE, 2017. http://dx.doi.org/10.1109/ifsa-scis.2017.8023334.

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Xiao, Chunyang, Marc Dymetman, and Claire Gardent. "Symbolic Priors for RNN-based Semantic Parsing." In Twenty-Sixth International Joint Conference on Artificial Intelligence. International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/585.

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Seq2seq models based on Recurrent Neural Networks (RNNs) have recently received a lot of attention in the domain of Semantic Parsing. While in principle they can be trained directly on pairs (natural language utterances, logical forms), their performance is limited by the amount of available data. To alleviate this problem, we propose to exploit various sources of prior knowledge: the well-formedness of the logical forms is modeled by a weighted context-free grammar; the likelihood that certain entities present in the input utterance are also present in the logical form is modeled by weighted

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Chiu, C. C., and C. Y. Liu. "Case Study of Program-Assisted Q-System Rating Based on Point Cloud Analysis." In 58th U.S. Rock Mechanics/Geomechanics Symposium. ARMA, 2024. http://dx.doi.org/10.56952/arma-2024-0164.

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ABSTRACT: This study develops a computer program to assist in rating the Q-system of jointed rock masses. The analysis is based on photogrammetric analysis of point clouds. Three key rating terms, rock quality designation (RQD), joint set number (Jn), and joint roughness number (Jr), can be calculated by the program without an expert's manual rating. To identify major outcrop joint surfaces, the random sample consensus algorithm was employed. Subsequently, we calculate the weighted joint density (wJd) and its corresponding RQD based on the major joint surface. The spherical K-means clustering

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