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Type-2 Tetradecagonal Fuzzy Number
2020This paper deals with a project construction of normal and crashing activity using type-2 tetradecagonal fuzzy number. Our aim is to obtain the total cost and completion time of the project. The working of the algorithm has been illustrated by numerical example.
A. Rajkumar, C. Sagaya Nathan Stalin
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Literature review on type-2 fuzzy set theory
Soft Computing - A Fusion of Foundations, Methodologies and Applications, 2022A. K. De, Debjani Chakraborty, A. Biswas
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Generalized Type-2 Fuzzy Logic
2017This Chapter describes the basic concepts about generalized type-2 fuzzy sets theory. We explain the generalized type-2 fuzzy system approximation based on α-planes including the fuzzifier process, fuzzy rules, inference engine, type reducer and defuzzification process; all these definitions are used to develop the fuzzy edge detection ...
Claudia I. Gonzalez +3 more
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Type-2 fuzzy probabilistic system
2012 9th International Conference on Fuzzy Systems and Knowledge Discovery, 2012The paper proposes a new type-2 fuzzy logic system, Type-2 Fuzzy Probabilistic System, coupled with type-2 fuzzy probability, to deal with higher order fuzzy events with fuzzy sub-events together. The new concepts of Membership Probability Density Function (Mpdf) and J-plane Representation for type-2 fuzzy set are also presented. A special Type-2 Fuzzy
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Interval type-2 fuzzy logic systems
Ninth IEEE International Conference on Fuzzy Systems. FUZZ- IEEE 2000 (Cat. No.00CH37063), 2000Q. Liang, J. Mendel
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From Type-2 Fuzzy to Type-2 Intervals and Type-2 Probabilities
Our knowledge comes from observations, measurements, and expert opinions. Measurements and observations are never 100% accurate, there is always a difference between the measurement result and the actual value of the corresponding quantity. We gauge the resulting uncertainty either by an interval of possible values, or by a probability distribution on ...Vladik Kreinovich +2 more
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2014
Latent Dirichlet allocation (LDA) is an important hierarchical Bayesian model for probabilistic topic modeling, which attracts worldwide interests and touches on many important applications in text mining, computer vision and computational biology. We first introduce a novel inference algorithm, called belief propagation (BP), for learning LDA, and ...
Jia Zeng, Zhi-Qiang Liu
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Latent Dirichlet allocation (LDA) is an important hierarchical Bayesian model for probabilistic topic modeling, which attracts worldwide interests and touches on many important applications in text mining, computer vision and computational biology. We first introduce a novel inference algorithm, called belief propagation (BP), for learning LDA, and ...
Jia Zeng, Zhi-Qiang Liu
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IEEE Transactions on Industrial Informatics, 2021
Shixi Hou, Yundi Chu, J. Fei
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Shixi Hou, Yundi Chu, J. Fei
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New Mathematics and Natural Computation
In this paper, an attempt is made to define a Type-2 fuzzy metric on a nonempty set [Formula: see text] by allowing it to take fuzzy numbers as values of distance of a pair of points under a membership grade which is also a fuzzy number. Its type-1 counterpart is a fuzzy metric mostly similar to those defined by Kramosil and Michalek [Formula: see ...
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In this paper, an attempt is made to define a Type-2 fuzzy metric on a nonempty set [Formula: see text] by allowing it to take fuzzy numbers as values of distance of a pair of points under a membership grade which is also a fuzzy number. Its type-1 counterpart is a fuzzy metric mostly similar to those defined by Kramosil and Michalek [Formula: see ...
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