Relevant bibliographies by topics / Fully Fuzzy Number

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Academic literature on the topic 'Fully Fuzzy Number'

Author: Grafiati
Published: 3 June 2025
Last updated: 19 July 2025

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Journal articles on the topic "Fully Fuzzy Number"

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R., Sophia Porchelvi, Uma S., and Irene Hepzibah R. "ON SOLVING FULLY FUZZY MULTI-OBJECTIVE LINEAR PROGRAMMING PROBLEM BY USING SYMMETRIC TRAPEZOIDAL FUZZY NUMBERS." International Journal of Current Research and Modern Education, Special Issue (August 14, 2017): 65–69. https://doi.org/10.5281/zenodo.842838.

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In this paper, a new approach for solving fully fuzzy multi-objective linear programming problem (FFMLPP) by using symmetric trapezoidal fuzzy numbers. Fuzzy arithmetic operations and simplex algorithm is proposed for solving fully fuzzy multi-objective linear programming problem with parameters represented by symmetric trapezoidal fuzzy numbers without converting it to crisp numbers. Using the proposed method the fuzzy optimal solution of fully fuzzy multi-objective linear programming problem can be easily obtained. Finally a numerical example is provided to check the efficiency of the propos
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Van Hop, Nguyen. "Solving fully fuzzy multi-objective linear programming problem with fuzzy dominant degrees." Journal of Intelligent & Fuzzy Systems 39, no. 3 (2020): 3577–95. http://dx.doi.org/10.3233/jifs-191888.

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In this paper, we investigate all relative relationships between two fuzzy numbers. Then, we introduce new relative measures to compare two fuzzy numbers instead of using absolute value to represent the fuzzy number. These measures address the dominant level that one fuzzy number is better than the other in terms of its position and shape. The so-called absolute fuzzy dominant degree and relative fuzzy dominant degree are developed to measure the differences between two fuzzy numbers applying for different types of constraint. These measures could capture all the shape’s characteristics and re
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Malkawi, G., N. Ahmad, and H. Ibrahim. "SOLVING THE FULLY FUZZY SYLVESTER MATRIX EQUATION WITH TRIANGULAR FUZZY NUMBER." Far East Journal of Mathematical Sciences (FJMS) 98, no. 1 (2015): 37–55. http://dx.doi.org/10.17654/fjmssep2015_037_055.

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Mehmood, Muhammad Athar, Muhammad Akram, Majed G. Alharbi, and Shahida Bashir. "Solution of Fully Bipolar Fuzzy Linear Programming Models." Mathematical Problems in Engineering 2021 (April 22, 2021): 1–31. http://dx.doi.org/10.1155/2021/9961891.

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The Yin-Yang bipolar fuzzy set is a powerful mathematical tool for depicting fuzziness and vagueness. We first extend the concept of crisp linear programming problem in a bipolar fuzzy environment based on bipolar fuzzy numbers. We first define arithmetic operations of unrestricted bipolar fuzzy numbers and multiplication of an unrestricted trapezoidal bipolar fuzzy number (TrBFN) with non-negative TrBFN. We then propose a method for solving fully bipolar fuzzy linear programming problems (FBFLPPs) with equality constraints in which the coefficients are unrestricted triangular bipolar fuzzy nu
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Fatimatuzzahra, Fatimatuzzahra, Aang Nuryaman, La Zakaria, and Agus Sutrisno. "SOLUTION OF FULLY FUZZY NONLINEAR EQUATION SYSTEMS USING GENETIC ALGORITHM." BAREKENG: Jurnal Ilmu Matematika dan Terapan 19, no. 2 (2025): 1169–78. https://doi.org/10.30598/barekengvol19iss2pp1169-1178.

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A system of nonlinear equations is a collection of several interrelated non-linear equations. Currently, systems of nonlinear equations are used not only on crisp but also on fuzzy numbers. A fuzzy number is an ordered pair function that has a degree of membership [0,1]. Meanwhile, a fully fuzzy system of equations is a system of equations that applies fuzzy number arithmetic operations. The solution of non-linear equation systems is usually complicated to solve analytically, so numerical methods are used as an alternative to solve these problems. In this research, the steps to find the soluti
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Das, Krishnapada. "On Fully Fuzzy Linear Programming Problems." International Journal of Science and Social Science Research 2, no. 3 (2024): 72–76. https://doi.org/10.5281/zenodo.14010593.

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The fuzzy linear programming problem has been used as an important tool in different disciplines such as engineering, business, economics, commerce, defence etc. Fully Fuzzy Linear Programming Problems (FFLP) are those in which all the parameters that is the cost coefficients, the technological coefficients, the right-hand side of the constraints, and the decision variable are fuzzy numbers. Ezzati et al. [1] suggested an algorithm to solve fully fuzzy linear programming problems. In this paper, we propose two methods to find the optimal solution of fully fuzzy linear programming pro
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Akram, Muhammad, Inayat Ullah, Tofigh Allahviranloo, and S. A. Edalatpanah. "LR-type fully Pythagorean fuzzy linear programming problems with equality constraints." Journal of Intelligent & Fuzzy Systems 41, no. 1 (2021): 1975–92. http://dx.doi.org/10.3233/jifs-210655.

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A Pythagorean fuzzy set is a powerful model for depicting fuzziness and uncertainty. This model is more flexible and practical as compared to an intuitionistic fuzzy model. This research article presents a new model called LR-type fully Pythagorean fuzzy linear programming problem. We consider the notions of LR-type Pythagorean fuzzy number, ranking for LR-type Pythagorean fuzzy numbers and arithmetic operations for unrestricted LR-type Pythagorean fuzzy numbers. We propose a method to solve LR-type fully Pythagorean fuzzy linear programming problems with equality constraints. We describe our
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JayanthKarthik, N., and E. Chandrasekaran. "Solving Fully Fuzzy Linear Systems with Trapezoidal Fuzzy Number Matrices by Partitioning." International Journal of Computer Applications 64, no. 9 (2013): 35–38. http://dx.doi.org/10.5120/10665-5438.

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Ren, Aihong. "A Novel Method for Solving the Fully Fuzzy Bilevel Linear Programming Problem." Mathematical Problems in Engineering 2015 (2015): 1–11. http://dx.doi.org/10.1155/2015/280380.

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We address a fully fuzzy bilevel linear programming problem in which all the coefficients and variables of both objective functions and constraints are expressed as fuzzy numbers. This paper is to develop a new method to deal with the fully fuzzy bilevel linear programming problem by applying interval programming method. To this end, we first discretize membership grade of fuzzy coefficients and fuzzy decision variables of the problem into a finite number ofα-level sets. By usingα-level sets of fuzzy numbers, the fully fuzzy bilevel linear programming problem is transformed into an interval bi
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Ghoushchi, Saeid Jafarzadeh, Elnaz Osgooei, Gholamreza Haseli, and Hana Tomaskova. "A Novel Approach to Solve Fully Fuzzy Linear Programming Problems with Modified Triangular Fuzzy Numbers." Mathematics 9, no. 22 (2021): 2937. http://dx.doi.org/10.3390/math9222937.

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Recently, new methods have been recommended to solve fully fuzzy linear programming (FFLP) issues. Likewise, the present study examines a new approach to solve FFLP issues through fuzzy decision parameters and variables using triangular fuzzy numbers. The strategy, which is based on alpha-cut theory and modified triangular fuzzy numbers, is suggested to obtain the optimal fully fuzzy solution for real-world problems. In this method, the problem is considered as a fully fuzzy problem and then is solved by applying the new definition presented for the triangular fuzzy number to optimize decision
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Books on the topic "Fully Fuzzy Number"

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Kotzen, Matthew. Probability in Epistemology. Edited by Alan Hájek and Christopher Hitchcock. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780199607617.013.32.

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In recent years, probabilistic approaches to epistemological questions have become increasingly influential. This chapter surveys a number of the most significant ways in which probability is relevant to contemporary epistemology. Topics surveyed include: the debate surrounding the connection between full and partial beliefs; synchronic rational constraints on credences including probabilism, regularity, reflection, and the principal principle; diachronic rational constraints on credences including conditionalization and de se updating; the application of the requirement of total evidence; evi
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Book chapters on the topic "Fully Fuzzy Number"

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Alrefaei, Mahmoud, Noor H. Ibrahim, and Marwa Tuffaha. "Solving fully fuzzy transportation problem with n-polygonal fuzzy numbers." In Proceedings of the 1st International Congress on Engineering Technologies. CRC Press, 2021. http://dx.doi.org/10.1201/9781003178255-25.

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Kaur, Amarpreet, Janusz Kacprzyk, and Amit Kumar. "New Methods for Solving Fully Fuzzy Solid Transshipment Problems with LR Flat Fuzzy Numbers." In Fuzzy Transportation and Transshipment Problems. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-26676-9_8.

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Kaur, Amarpreet, Janusz Kacprzyk, and Amit Kumar. "New Methods for Solving the Fully Fuzzy Transportation Problems with the LR Flat Fuzzy Numbers." In Fuzzy Transportation and Transshipment Problems. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-26676-9_5.

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Zhang, Keke, Xu Chen, Yongjun Jing, Shuyang Wang, and Lijun Tang. "Research on Named Entity Recognition Method of Network Threat Intelligence." In Communications in Computer and Information Science. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-8285-9_16.

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AbstractWith the continuous emergence of new network threat means, how to turn passive defense into active prediction, the rise of Cyber Threat Intelligence (CTI) technology provides a new idea. CTI technology can timely and effectively obtain all kinds of network security threat intelligence information to help security personnel quickly identify all kinds of attacks and make effective decisions in time. However, there are not only a large number of redundant information in threat intelligence information, but also the problems of Chinese English mixing, fuzzy boundary, and polysemy of related security entities. Therefore, identifying complex and valuable information from this information has become a great challenge. Through the research on the above problems, a named entity recognition model in the field of Network Threat Intelligence Based on BERT-BiLSTM-Self-Attention-CRF is proposed to identify the complex network threat intelligence entities in the text. Firstly, the dynamic word vector is obtained through Bert to fully represent the semantic information and solve the problem of polysemy of a word. Then the obtained word vector is used as the input of BiLSTM, and the context feature vector is obtained by BiLSTM. Then the output result is introduced into the self-attention mechanism to capture the correlation within the data or features, and finally the result is input into CRF for annotation. To verify the effectiveness of the model, experiments are carried out on the constructed network threat intelligence data set. The results show that the model significantly improves the effect of Threat Intelligence named entity recognition compared with several other classical models.
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Kaur, Jagdeep, and Amit Kumar. "Fuzzy Optimal Solution of Fully Fuzzy Linear Programming Problems with Equality Constraints Having LR Flat Fuzzy Numbers." In An Introduction to Fuzzy Linear Programming Problems. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-31274-3_4.

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Kaur, Jagdeep, and Amit Kumar. "Fuzzy Optimal Solution of Fully Fuzzy Linear Programming Problems with Inequality Constraints Having LR Flat Fuzzy Numbers." In An Introduction to Fuzzy Linear Programming Problems. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-31274-3_5.

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Kumar, Amit, Parmpreet Kaur, and Jagdeep Kaur. "Fuzzy Optimal Solution of Fully Fuzzy Project Crashing Problems with New Representation of LR Flat Fuzzy Numbers." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-21881-1_28.

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Kaur, Amarpreet, Janusz Kacprzyk, and Amit Kumar. "New Improved Methods for Solving the Fully Fuzzy Transshipment Problems with Parameters Given as the LR Flat Fuzzy Numbers." In Fuzzy Transportation and Transshipment Problems. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-26676-9_6.

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Kaur, Jagdeep, and Amit Kumar. "Unique Fuzzy Optimal Value of Fully Fuzzy Linear Programming Problems with Equality Constraints Having LR Flat Fuzzy Numbers." In An Introduction to Fuzzy Linear Programming Problems. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-31274-3_6.

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Muralidaran, C., and B. Venkateswarlu. "Direct Solving Method of Fully Fuzzy Linear Programming Problems with Equality Constraints Having Positive Fuzzy Numbers." In Trends in Mathematics. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-01120-8_34.

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Conference papers on the topic "Fully Fuzzy Number"

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Kalyani, S., and S. Nagarani. "A fully fuzzy transportation problem with hexagonal fuzzy number." In PROCEEDINGS OF INTERNATIONAL CONFERENCE ON ADVANCES IN MATERIALS RESEARCH (ICAMR - 2019). AIP Publishing, 2020. http://dx.doi.org/10.1063/5.0016903.

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Sangal, Atul, and Rajesh Kumar Saini. "Fully Fuzzy Transportation Problem with Heptagonal Intutionistic Fuzzy Number." In 2018 4th International Conference on Computing Communication and Automation (ICCCA). IEEE, 2018. http://dx.doi.org/10.1109/ccaa.2018.8777653.

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Malkawi, Ghassan, Ibrahim Rida, and Nazihah Ahmad. "An associated linear system approach for solving fully fuzzy linear system with hexagonal fuzzy number." In 2018 Advances in Science and Engineering Technology International Conferences (ASET). IEEE, 2018. http://dx.doi.org/10.1109/icaset.2018.8376919.

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Malkawi, Ghassan, Ibrahim Rida, and Nazihah Ahmad. "An associated linear system approach for solving fully fuzzy linear system with hexagonal fuzzy number." In 2018 Advances in Science and Engineering Technology International Conferences (ASET). IEEE, 2018. http://dx.doi.org/10.1109/icaset.2018.8376930.

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Yang, Xiao-Peng, Bing-Yuan Cao, and Hai-Tao Lin. "Multi-objective fully fuzzy linear programming problems with triangular fuzzy numbers." In 2014 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD). IEEE, 2014. http://dx.doi.org/10.1109/fskd.2014.6980827.

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Gong, Zeng-Tai, and Kun Liu. "Fuzzy approximate solution of general fully fuzzy linear systems based on GLR-fuzzy numbers." In 2010 International Conference on Machine Learning and Cybernetics (ICMLC). IEEE, 2010. http://dx.doi.org/10.1109/icmlc.2010.5580538.

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Zhang, Peng, Jianye Hao, Weixun Wang, et al. "KoGuN: Accelerating Deep Reinforcement Learning via Integrating Human Suboptimal Knowledge." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/317.

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Reinforcement learning agents usually learn from scratch, which requires a large number of interactions with the environment. This is quite different from the learning process of human. When faced with a new task, human naturally have the common sense and use the prior knowledge to derive an initial policy and guide the learning process afterwards. Although the prior knowledge may be not fully applicable to the new task, the learning process is significantly sped up since the initial policy ensures a quick-start of learning and intermediate guidance allows to avoid unnecessary exploration. Tak
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Hollick, Joshua, Ingrid Jafari, Roberto Togneri, and Sven Nordholm. "Source number estimation in reverberant conditions via full-band weighted, adaptive fuzzy c-means clustering." In ICASSP 2014 - 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2014. http://dx.doi.org/10.1109/icassp.2014.6855048.

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Law, William S., and Erik K. Antonsson. "Multi-Dimensional Mapping of Design Imprecision." In ASME 1996 Design Engineering Technical Conferences and Computers in Engineering Conference. American Society of Mechanical Engineers, 1996. http://dx.doi.org/10.1115/96-detc/dtm-1524.

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Abstract Preliminary design information is characteristically imprecise or fuzzy: specifications and requirements are subject to change, and the design description is vague and incomplete. The Method of Imprecision uses the mathematics of fuzzy sets to explicitly represent and manipulate imprecise preliminary design information, enabling the designer to better understand the full range of designs and performances that satisfy an imprecise set of specifications and requirements. This paper discusses the foundations of this methodology, and introduces pragmatic extensions that provide computatio
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Liu, Shi, and Liangsheng Qu. "Application of Adaptive Neuro-Fuzzy Inference System in Field Balancing." In ASME 2005 International Mechanical Engineering Congress and Exposition. ASMEDC, 2005. http://dx.doi.org/10.1115/imece2005-80367.

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The field balancing of flexible rotors is one of the key techniques to reduce vibration of large rotating machinery. Although in recent decades the balancing theory has been thoroughly studied and various balancing techniques have been well developed, the present balancing methods are still remain for further improvements in accuracy and efficiency. Firstly, most balancing methods need large numbers of trial runs to obtain the vibration responses of trial weights in different correcting planes. Secondly, the vibration response in each measured section is always taken from a single sensor, and
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