Abstract
The scientific term neutrosophy was first coined by Florentin Smarandache a few years ago. The origins, attribute, extent of neutralities and their interactions with other ideational spectra, and indeterminacy are all investigated in this discipline of study. Neutrosophic logic, a group of many-valued systems which can be regarded as an extension of fuzzy logic, is one of the new theories based on the fundamental principles of neutrosophy. Neutrosophy logic is a new branch of logic that addresses the shortcomings of fuzzy and classical logic. Some of the disadvantages of fuzzy relations are failures to handle inconsistent information and the high processing cost of completing a non-linear program. In neutrosophic sets, truthfulness and falsity are independent, whereas in intuitionistic fuzzy sets, it is dependent. The neutrosophic logic has the ability to manipulate both incomplete and inconsistent data. So, there is a need for research into the use of neutrosophic logic in different domains from medical treatment to the role of a recommender system using new advanced computational intelligent techniques. In this study, we are discussing about basic concepts of neutrosophic logic, fuzzy logic’s drawbacks and advantages of using neutrosophic logic, and also the comparison between neutrosophic logic, intuitionistic and interval-valued fuzzy systems, and classical logic on different factors like uncertainty and vagueness.
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References
Rivieccio, U.: Neutrosophic logics: prospects and problems. Fuzzy Sets Syst. 159(14) (2008). https://doi.org/10.1016/j.fss.2007.11.011
Ansari, A.Q., Biswas, R., Aggarwal, S.: Neutrosophic classifier: an extension of fuzzy classifier. Appl. Soft Comput. 13(1), 563–573 (2013). https://doi.org/10.1016/j.asoc.2012.08.002
Gafar, M.G., Elhoseny, M., Gunasekaran, M.: Modelingneutrosophic variables based on particle swarm optimization and information theory measures for forest fires. J. Supercomput. 76, 2339–2356 (2020). https://doi.org/10.1007/s11227-018-2512-5
Atanassov, K.T.: Intuitionistic fuzzy sets. Physica-Verlag, Heidelberg (1999)
Priest, G., Tanaka, K., Weber, Z.: Para consistent logic. In: Zalta, E.N. (ed) The Stanford Encyclopedia of Philosophy (Summer 2018 Edition). https://plato.stanford.edu/archives/sum2018/entries/logic-paraconsistent/
Abdel-Basset, M., Manogaran, G., Gamal, A., Smarandache, F.: A hybrid approach of neutrosophic sets and DEMATEL method for developing supplier selection criteria. Des. Autom. Embedded Syst. 22(3), 257–278 (2018)
Smarandache, F.: A unifying field in logics: neutrosophic logic. In: Neutrosophy, Neutrosophic Set, Neutrosophic Probability: Neutrosophic Logic. Neutrosophy, Neutrosophic Set, Neutrosophic Probability. Infinite Study. American Research Press, Santa Fe (2005)
Smarandache, F. (ed.), Proceedings of the First International Conference on Neutrosophy, Neutrosophic logic, Neutrosophic Set, Neutrosophic Probability and Statistics. University of New Mexico, Gallup Campus, Xiquan, Phoenix, p. 147 (2002)
Smarandache, F., Leyva-Vázquez, M.: Fundamentals of neutrosophic logic and sets and their role in artificial intelligence. Journal contribution (2018). https://doi.org/10.6084/m9.figshare.7048106.v1
Kavitha, B., Karthikeyan, S., Sheeba Maybell, P.: An ensemble design of intrusion detection system for handling uncertainty using neutrosophic logic classifier. Know.-Based Syst. 28, 88–96 (2012). https://doi.org/10.1016/j.knosys.2011.12.004
Radwan, N., BadrSenousy, M., Riad, A.E.D.M.: Neutrosophic logic approach for evaluating learning management systems. Neutrosophic Sets Syst. 11, 3–7 (2016)
Broumi, S., Lathamaheswari, M., Bakali, A., Talea, M., Smarandache, F., Nagarajan, D., Kavikumar, K., Asmae, G.: Analyzing age group and time of the day using interval valued neutrosophic sets. Neutrosophic Sets Syst. 32, 1 (2020)
Alzadjali, N., Jereesha, M.S., Savarimuthu, C., Divyajyothi, M.G.: A recommender system for Alzheimer patients in sultanate of Oman using neutrosophic logic. In: 2020 International Conference on Emerging Trends in Information Technology and Engineering (ic-ETITE), pp. 1–5 (2020)
Sivaranjani, S., et al.: Breast cancer detection using neutrosophic logic. Int. J. Fut. Gener. Commun. Netw. 12(5) (2019)
Gaber, T., et al.: Thermogram breast cancer prediction approach based on neutrosophic sets and fuzzy c-means algorithm. In: 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 4254–4257 (2015). https://doi.org/10.1109/EMBC.2015.7319334
Zhang, H., Wang, J., Chen, X.: Interval neutrosophic sets and their application in multicriteria decision making problems. Sci. World J. 2014. Article ID 645953, 15 p (2014)
Lupiáñez, F.G.: On neutrosophic sets and topology. Procedia Comput. Sci. 120, 975–982 (2017). https://doi.org/10.1016/j.procs.2018.01.090
Koundal, D., Sharma, B.: 15-challenges and future directions in neutrosophic set-based medical image analysis. In: Neutrosophic Set in Medical Image Analysis. Academic Press, pp. 313–343 (2019)
Smarandache, F., Vlădăreanu, L.: Applications of neutrosophic logic to robotics: An introduction. IEEE International Conference on Granular Computing 2011, 607–612 (2011). https://doi.org/10.1109/GRC.2011.6122666
Sharma, M., Kandasamy, I., Vasantha, W.B.: Comparison of neutrosophic approach to various deep learning models for sentiment analysis. Knowl. Based Syst. 223, 107058 (2021). ISSN 0950-7051. https://doi.org/10.1016/j.knosys.2021.107058
Hezam, I.M., Nayeem, M.K., Foul, A., Alrasheedi, A.F.: COVID-19 vaccine: a neutrosophic MCDM approach for determining the priority groups. Results Phys. 20, 103654 (2021). ISSN 2211–3797. https://doi.org/10.1016/j.rinp.2020.103654
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Mallik, S., Mohanty, S., Mishra, B.S. (2022). Neutrosophic Logic and Its Scientific Applications. In: Dehuri, S., Prasad Mishra, B.S., Mallick, P.K., Cho, SB. (eds) Biologically Inspired Techniques in Many Criteria Decision Making. Smart Innovation, Systems and Technologies, vol 271. Springer, Singapore. https://doi.org/10.1007/978-981-16-8739-6_38
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