Relevant bibliographies by topics / Fuzzy parameterized soft set

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  2. Dissertations / Theses
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Academic literature on the topic 'Fuzzy parameterized soft set'

Author: Grafiati
Published: 4 June 2025
Last updated: 1 August 2025

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Journal articles on the topic "Fuzzy parameterized soft set"

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P., Thirunavukarasu, and Suresh R. "Parameterized Soft Complex Fuzzy Sets." Journal of Progressive Research in Mathematics 4, no. 2 (2015): 303–8. https://doi.org/10.5281/zenodo.3980480.

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In this paper, we presents a new concept of parameterized soft complex fuzzy set (pscf-set) which is generalized from the innovative concept of a complex fuzzy set by adding phase term to the definition of fuzzy set. Various operators with examples of pscf-set provided in this paper. We then define a pscf-set aggregation operator.
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E., E. Edeghagba, I. Abubakar S., M. Umar F., and Abdullahi M. "Full Fuzzy parameterized Soft Expert Set with Application to Decision Making." International Journal of Mathematical Sciences and Optimization: Theory and Applications 10, no. 4 (2024): 12–28. https://doi.org/10.5281/zenodo.14685917.

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In this work, the authors consider a generalization of fuzzy parameterized soft expert set introducing the concept of full fuzzy parameterized soft expert set and study their properties. We define its basic operations and develop an algorithm to demonstrate its application in decision making. We also define the optimal choice object, developing and proving propositions relating to it. Finally, we use a concrete example to illustrate our algorithm.
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Atiqe, Ur Rahman, Saeed Muhammad, and Zahid Saba. "Application in decision making based on fuzzy parameterized hypersoft set theory." Asia Mathematika 5, no. 1 (2021): 19–27. https://doi.org/10.5281/zenodo.4721481.

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Hypersoft set is the generalization of the soft set as it converts single attribute function to multi-attribute function. The core purpose of this study is to make the existing literature regarding fuzzy parameterized soft set in line with the need for multi-attribute function. We first conceptualize the fuzzy parameterized hypersoft set along with some of its fundamentals. Then we propose a decision-making-based algorithm with the help of this theory. Moreover, an illustrative example is presented which depicts its validity for successful application to the problems involving vagueness and un
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Bashir, Maruah, and Abdul Razak Salleh. "Fuzzy Parameterized Soft Expert Set." Abstract and Applied Analysis 2012 (2012): 1–15. http://dx.doi.org/10.1155/2012/258361.

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In 2011 Alkhazaleh and Salleh introduced the concept of soft expert set and gave an application in a decision-making problem. In this paper we introduce the concept of fuzzy parameterized soft expert set by giving an important degree for each element in the set of parameters. We also study its properties and define its basic operations, namely, complement, union, intersection, AND, and OR. Finally, we give an application in decision making.
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Atiqe, Ur Rahman, Saeed Muhammad, and Abd El-Wahed Khalifa Hamiden. "Decision making application based on parameterization of fuzzy hypersoft set with fuzzy setting." Italian Journal of Pure and Applied Mathematics 48 (October 13, 2022): 1033–48. https://doi.org/10.5281/zenodo.7477708.

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Fuzzy soft set is considered as an apt parameterization tool to deal with vagueness and uncertainties. There are many situations when attributes need to be further classified into attribute-valued disjoint sets. Such situations are not tackled by the existing fuzzy soft-like structures. Hypersoft set, an extension of soft set, employs multi-argument approximate function which addresses the inadequacy of existing structures for attribute-valued disjoint sets. In this study, theory of fuzzy parameterized fuzzy hypersoft set is characterized and some of its essential properties are discussed. In
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Hassan, Nasruddin, and Yousef Al-Qudah. "Fuzzy parameterized complex multi-fuzzy soft set." Journal of Physics: Conference Series 1212 (April 2019): 012016. http://dx.doi.org/10.1088/1742-6596/1212/1/012016.

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Edeghagba, Elijah E., and Umar F. Muhammad. "On Full Fuzzy Parameterized Soft Set." International Journal of Mathematical Analysis and Optimization: Theory and Applications 7, no. 2 (2022): 76–87. http://dx.doi.org/10.52968/28302774.

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Some Years back, researchers made attempts in trying to fuzzify set of parameters of soft set. In this paper, we consider a review of “fuzzy parameterized soft set", and improve it by introducing a way to fully fuzzify the set of parameters of soft set. We define the concept “full fuzzy parametrized soft set" and study some of its basic operations. We also illustrate the concept with example.
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Sari, Fitria Winda. "Himpunan Kabur Lembut Berparameter Kabur dan Aplikasinya." Jurnal Matematika UNAND 4, no. 4 (2019): 173. http://dx.doi.org/10.25077/jmu.4.4.173-185.2015.

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Pada tulisan ini akan diperkenalkan Himpunan Kabur Lembut Berparameter Kabur (FPSF) dan beberapa sifat-sifat aljabarnya. Selanjutnya juga diperkenalkan operator aggregate dari himpunan FPSF, yang digunakan untuk pengambilan keputusan. Pada akhirnya dengan menerapkan himpunan FPSF dan operator aggregate FPSF, didapatkan algoritma dalam pengambilan keputusan yang digunakan untuk membuat model peringatan banjir dan cara memilih juri yang terbaik dalam memberikan penilaian pada seorang peserta lomba.Kata Kunci: Soft Set, Fuzzy Set, Fuzzy Soft Set, Fuzzy Parameterized Soft Set, Fuzzy Parameterized
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Anwar, Anwar, and Ayman A. Hazaymeh. "Time Fuzzy Parameterized Fuzzy Soft Expert Sets." International Journal of Neutrosophic Science 25, no. 4 (2025): 101–21. https://doi.org/10.54216/ijns.250409.

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Finally In this study, we define parameterized time fuzzy soft expert set (PTFSES) as an extension of fuzzy soft set. Additionally, we will clarify and investigate the characteristics of its primary operation (complement, union intersection, ”AND” and ”OR”). , we’ll apply this approach to decision-making difficulties.
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Das, Ajoy Kanti, and Carlos Granados. "FP-intuitionistic multi fuzzy N-soft set and its induced FP-Hesitant N soft set in decision-making." Decision Making: Applications in Management and Engineering 5, no. 1 (2022): 67–89. http://dx.doi.org/10.31181/dmame181221045d.

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Intuitionistic fuzzy sets (IFSs) can effectively represent and simulate the uncertainty and diversity of judgment information offered by decision-makers (DMs). In comparison to fuzzy sets (FSs), IFSs are highly beneficial for expressing vagueness and uncertainty more accurately. As a result, in this research work, we offer an approach for solving group decision-making problems (GDMPs) with fuzzy parameterized intuitionistic multi fuzzy N-soft set (briefly, FPIMFNSS) of dimension q by introducing its induced fuzzy parameterized hesitant N-soft set (FPHNSS) as an extension of the multi-fuzzy N-s
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Dissertations / Theses on the topic "Fuzzy parameterized soft set"

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Abbas, Mujahid. "Soft Set Theory: Generalizations, Fixed Point Theorems, and Applications." Doctoral thesis, Universitat Politècnica de València, 2015. http://hdl.handle.net/10251/48470.

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Mathematical models have extensively been used in problems related to engineering, computer sciences, economics, social, natural and medical sciences etc. It has become very common to use mathematical tools to solve, study the behavior and different aspects of a system and its different subsystems. Because of various uncertainties arising in real world situations, methods of classical mathematics may not be successfully applied to solve them. Thus, new mathematical theories such as probability theory and fuzzy set theory have been introduced by mathematicians and computer scientists to
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Saeed, Mehreen. "Soft AI methods and visual speech recognition." Thesis, University of Bristol, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.299270.

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Hill, Carla. "Mass assignments for inductive logic programming." Thesis, University of Bristol, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.325748.

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Chung, Hsiang-Yu, and 鍾翔宇. "Integrating soft set and fuzzy linguistic model to evaluate maintenance and operating decisions of training simulation systems." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/rgeaqa.

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博士<br>國立交通大學<br>工業工程與管理系所<br>106<br>The advancement of high technologies and the arrival of the information age have caused changes to the modern warfare; more technologically exquisite weapons are designed, increasing in cost and complexity. Training maneuvers with live ammunition are expensive and are prone to accidental casualties. Thus, the military forces of many countries have replaced partially real training drills with training simulation systems to achieve combat readiness. Although considerable types of training simulation systems are used in military settings, the training effective
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Hsu, Hua-Chi, and 徐華騏. "Stream flood forecasting using a soft-computing approach (neural networks and fuzzy set theory)--A case study of Wu-Tu basin." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/93037991270334908944.

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碩士<br>清雲科技大學<br>土木與防災研究所<br>96<br>The weather in Taiwan is high precipitation, and the heavy rainfall is generally in the typhoon season. Therefore, how to forecast stream flow is a worthy research subject for hydraulic engineers to avoid damages by typhoon. In this study, a flow-trend index based on the fuzzy set theory is developed for neural network models to systematically establish the relationship between the rainfall history and stream flow. The precipitation records of Wu-Tu including 18 typhoon events from 1973 to 2001 are used to train and test the stream flow forecasting model. The
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Shu, Hua-Chi, and 徐華騏. "Stream flood forecasting using a soft-computing approach (neural networks and fuzzy set theory)--A case study of Wu-Tu basin." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/08429472489760610812.

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碩士<br>清雲科技大學<br>空間資訊與防災科技研究所<br>96<br>The weather in Taiwan is high precipitation, and the heavy rainfall is generally in the typhoon season. Therefore, how to forecast stream flow is a worthy research subject for hydraulic engineers to avoid damages by typhoon. In this study, a flow-trend index based on the fuzzy set theory is developed for neural network models to systematically establish the relationship between the rainfall history and stream flow. The precipitation records of Wu-Tu including 18 typhoon events from 1973 to 2001 are used to train and test the stream flow forecasting model.
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Rautenbach, Helperus Ritzema. "An empirically derived system for high-speed rendering." Thesis, 2012. http://hdl.handle.net/2263/28196.

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This thesis focuses on 3D computer graphics and the continuous maximisation of rendering quality and performance. Its main focus is the critical analysis of numerous real-time rendering algorithms and the construction of an empirically derived system for the high-speed rendering of shader-based special effects, lighting effects, shadows, reflection and refraction, post-processing effects and the processing of physics. This critical analysis allows us to assess the relationship between rendering quality and performance. It also allows for the isolation of key algorithmic weaknesses and possible
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Books on the topic "Fuzzy parameterized soft set"

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International Conference on Rough Sets, Fuzzy Sets and Soft Computing (2009 Dept. of Mathematics, Tripura University). Proceedings, International Conference on Rough Sets, Fuzzy Sets, and Soft Computing, November 5-7, 2009. Serials Publications, 2011.

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1964-, Feuring Thomas, ed. Fuzzy and neural: Interactions anmd applications. Physica-Verlag, 1999.

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North American Fuzzy Information Processing Society. Conference. 18th International Conference of the North American Fuzzy Information Processing Society--NAFIPS: June 10-12, 199 [sic], New York, New York, U.S.A. Institute of Electrical and Electronics Engineers, 1999.

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1944-, Nguyen Hung T., ed. A first course in fuzzy and neural control. Chapman & Hall/CRC Press, 2003.

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1944-, Nguyen Hung T., ed. A first course in fuzzy and neural control. Chapman & Hall/CRC Press, 2003.

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Huang, Chongfu. Towards efficient fuzzy information processing: Using the principle of information diffusion. Physica-Verlag, 2002.

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Halder, S. Bhattacharya. Rough Sets, Fuzzy Sets and Soft Computing. Narosa Publishing House, 2015.

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An Introduction to Fuzzy Logic and Fuzzy Sets (Advances in Soft Computing). Physica-Verlag Heidelberg, 2002.

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Orlowska, Ewa. Incomplete Information: Rough Set Analysis. Physica-Verlag, 2013.

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Similarity and Compatibility in Fuzzy Set Theory Studies in Fuzziness and Soft Computing. Physica-Verlag HD, 2010.

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Book chapters on the topic "Fuzzy parameterized soft set"

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Rajput, Laxmi, and Sanjay Kumar. "Spherical Fuzzy Parameterized Soft Set-Based Multi-criteria Decision-Making Method." In Algorithms for Intelligent Systems. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-7041-2_38.

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Mukherjee, Anjan. "IF Parameterised Intuitionistic Fuzzy Soft Set Theories on Decisions-Making." In Generalized Rough Sets. Springer India, 2015. http://dx.doi.org/10.1007/978-81-322-2458-7_10.

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Shanahan, James G. "Fuzzy Set Theory." In Soft Computing for Knowledge Discovery. Springer US, 2000. http://dx.doi.org/10.1007/978-1-4615-4335-0_3.

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Chakrabarty, Kankana. "Roughness Indicator Fuzzy Set." In Developments in Soft Computing. Physica-Verlag HD, 2001. http://dx.doi.org/10.1007/978-3-7908-1829-1_7.

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Al-Hijjawi, Sumyyah, and Shawkat Alkhazaleh. "Effective Time Fuzzy Soft Set." In Springer Proceedings in Mathematics & Statistics. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-4876-1_9.

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Jayanthiladevi, A., L. Devi, R. Kannadasan, Ved P. Mishra, Piyush Mishra, and A. Mohamed Uvaze Ahamed. "Implying Fuzzy Set for Computing Agricultural Vulnerability." In Applied Soft Computing. Apple Academic Press, 2021. http://dx.doi.org/10.1201/9781003186885-14.

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Raha, Swapan, and Sanaul Hossain. "Fuzzy Set in Default Reasoning." In Advances in Soft Computing — AFSS 2002. Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-45631-7_4.

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Yao, Dengbao, Cuicui Wang, Junjun Mao, and Yanping Zhang. "Granularity Analysis of Fuzzy Soft Set." In Rough Sets and Knowledge Technology. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31900-6_50.

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Zhao, Xiao-yan, Jian-guo Xu, and Jing-gui Gao. "An Extension of Rough Fuzzy Set on the Fuzzy Approximation Space." In Advances in Soft Computing. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-03664-4_68.

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Niskanen, Vesa A. "Brief Introduction to Fuzzy Set Theory." In Soft Computing Methods in Human Sciences. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-36421-4_2.

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Conference papers on the topic "Fuzzy parameterized soft set"

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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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Yao, Bing-xue, Jin-liang Liu, and Rui-xia Yan. "Fuzzy Soft Set and Soft Fuzzy Set." In 2008 Fourth International Conference on Natural Computation. IEEE, 2008. http://dx.doi.org/10.1109/icnc.2008.137.

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Al-Qudah, Yousef, and Nasruddin Hassan. "Fuzzy parameterized complex multi-fuzzy soft expert sets." In THE 2018 UKM FST POSTGRADUATE COLLOQUIUM: Proceedings of the Universiti Kebangsaan Malaysia, Faculty of Science and Technology 2018 Postgraduate Colloquium. AIP Publishing, 2019. http://dx.doi.org/10.1063/1.5111229.

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Fu Li and Wang Pingshu. "Comparison of the concepts of soft set, fuzzy soft set and L-fuzzy set." In 2011 Eighth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2011). IEEE, 2011. http://dx.doi.org/10.1109/fskd.2011.6019607.

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Xu, Yong-jie, Yong-kan Sun, and Deng-feng Li. "Intuitionistic Fuzzy Soft Set." In 2010 2nd International Workshop on Intelligent Systems and Applications (ISA). IEEE, 2010. http://dx.doi.org/10.1109/iwisa.2010.5473444.

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YANG, HAI-LONG. "ON FUZZY SOFT SET RELATIONS." In Proceedings of the QL&SC 2012. WORLD SCIENTIFIC, 2012. http://dx.doi.org/10.1142/9789814401531_0083.

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Jiang, Yi, Hailiang Zhao, and Junxuan He. "The relation between fuzzy soft set and integrative fuzzy set." In 2017 12th International Conference on Intelligent Systems and Knowledge Engineering (ISKE). IEEE, 2017. http://dx.doi.org/10.1109/iske.2017.8258761.

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Khan, Muhammad Sadiq, and Tutut Herawan. "Substantial Differences between Fuzzy Set and Soft Set Theories." In 3rd International Conference of Computer, Environment, Agriculture, Social Science, Health Science, Engineering and Technology. SCITEPRESS - Science and Technology Publications, 2018. http://dx.doi.org/10.5220/0010043403840387.

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Yanto, Iwan Tri Riyadi, Edi Sutoyo, Ani Apriani, and Okki Verdiansyah. "Fuzzy Soft Set for Rock Igneous Clasification." In 2018 International Symposium on Advanced Intelligent Informatics (SAIN). IEEE, 2018. http://dx.doi.org/10.1109/sain.2018.8673383.

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Ma, Xir;ao, and Guoyin Wang. "An extended soft set model: Type-2 fuzzy soft sets." In 2011 IEEE International Conference on Cloud Computing and Intelligence Systems (CCIS). IEEE, 2011. http://dx.doi.org/10.1109/ccis.2011.6045046.

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