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picture-Neutrosophic Trusted Safe Semi-Supervised fuzzy Clustering for Noisy Data

Computer Systems Science & Engineering 2023年第8期46卷 1981-1997页

作者： Pham Huy Thong Florentin Smarandache Phung The Huan Tran Manh Tuan Tran Thi Ngan Vu Duc Thai Nguyen Long Giang Le Hoang Son Graduate University of Science and Technology Vietnam Academy of Science and TechnologyHanoi100000Vietnam Institute of Information Technology Vietnam Academy of Science and TechnologyHanoi100000Vietnam VNU Information Technology Institute Vietnam National UniversityHanoi100000Vietnam Department of Mathematics University of New MexicoGallup87301New MexicoUSA University of Information and Communication Technology Thai Nguyen UniversityThai Nguyen250000Vietnam Faculty of Computer Science and Engineering Thuyloi UniversityHanoi100000Vietnam

Clustering is a crucial method for deciphering data structure and producing new *** to its significance in revealing fundamental connections between the human brain and events,it is essential to utilize clustering for cognitive *** with noisy data caused by inaccurate synthesis from several sources or misleading data production processes is one of the most intriguing clustering *** data can lead to incorrect object recognition and *** research aims to innovate a novel clustering approach,named picture-Neutrosophic Trusted Safe Semi-Supervised fuzzy Clustering(PNTS3FCM),to solve the clustering problem with noisy data using neutral and refusal degrees in the definition of picture fuzzy set(PFS)and Neutrosophic set(NS).Our contribution is to propose a new optimization model with four essential components:clustering,outlier removal,safe semi-supervised fuzzy clustering and partitioning with labeled and unlabeled *** effectiveness and flexibility of the proposed technique are estimated and compared with the state-of-art methods,standard picture fuzzy clustering(FC-PFS)and Confidence-weighted safe semi-supervised clustering(CS3FCM)on benchmark UCI *** experimental results show that our method is better at least 10/15 datasets than the compared methods in terms of clustering quality and computational time.

关键词： Safe semi-supervised fuzzy clustering picture fuzzy set neutrosophic set data partition with noises fuzzy clustering

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Characterisations of semigroups by the properties of their picture fuzzy bi-ideals

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Journal of Control and Decision 2022年第1期9卷 111-116页

作者： Pairote Yiarayong Department of Mathematics Faculty of Science and TechnologyPibulsongkram Rajabhat UniversityPhitsanulokThailand

In this article,a new generalisation of fuzzy bi-ideals and intuitionsitic fuzzy bi-ideals of a semigroup considered so called picture fuzzy bi-ideals no a *** is well known that the intra-regular semigroups play an essential role in studying the structure,especially the decomposition,of *** purpose of this paper is to deal with the algebraic structure of semigroups by applying picture fuzzy set *** an application of our results we get characterisations of intra-regular regular semigroups in terms of picture fuzzy *** prove that a semigroup is both regular and intra-regular if and only if every picture fuzzy bi-ideal on S is idempotent.

关键词： Intra-regular semigroup left quasi-regular semigroup picture fuzzy bi-ideal picture fuzzy set weakly regular semigroup

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Arithmetic Operations of Generalized Trapezoidal picture fuzzy Numbers by Vertex Method

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American Journal of Computational Mathematics 2023年第1期13卷 99-121页

作者： Mohammad Kamrul Hasan Abeda Sultana Nirmal Kanti Mitra Department of Mathematics Jahangirnagar University Savar Bangladesh Department of Mathematics and Statistics Bangladesh University of Business and Technology Dhaka Bangladesh

In this article, we define the arithmetic operations of generalized trapezoidal picture fuzzy numbers by vertex method which is assembled on a combination of the (α, γ, β)-cut concept and standard interval analysis. Various related properties are explored. Finally, some computations of picture fuzzy functions over generalized picture fuzzy variables are illustrated by using our proposed technique.

关键词： picture fuzzy set Generalized Trapezoidal picture fuzzy Number (α γ β)-Cut Arithmetic Operations Vertex Method

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