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  • Open Access

    ARTICLE

    A Novel Incremental Attribute Reduction Algorithm Based on Intuitionistic Fuzzy Partition Distance

    Pham Viet Anh1,3, Nguyen Ngoc Thuy4, Nguyen Long Giang2, Pham Dinh Khanh5, Nguyen The Thuy1,6,*

    Computer Systems Science and Engineering, Vol.47, No.3, pp. 2971-2988, 2023, DOI:10.32604/csse.2023.042068 - 09 November 2023

    Abstract Attribute reduction, also known as feature selection, for decision information systems is one of the most pivotal issues in machine learning and data mining. Approaches based on the rough set theory and some extensions were proved to be efficient for dealing with the problem of attribute reduction. Unfortunately, the intuitionistic fuzzy sets based methods have not received much interest, while these methods are well-known as a very powerful approach to noisy decision tables, i.e., data tables with the low initial classification accuracy. Therefore, this paper provides a novel incremental attribute reduction method to deal more… More >

  • Open Access

    ARTICLE

    Business Blockchain Suitability Determinants: Decision-Making through an Intuitionistic Fuzzy Method

    Tomader Almeshal1,*, Jawad Berri1, Tarifa Almulhim2, Areej Alhogail1, Emam Ahmed3

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 1665-1690, 2023, DOI:10.32604/csse.2023.038871 - 28 July 2023

    Abstract Blockchain is one of the innovative and disruptive technologies that has a wide range of applications in multiple industries beyond cryptocurrency. The widespread adoption of blockchain technology in various industries has shown its potential to solve challenging business problems, as well as the possibility to create new business models which can increase a firm’s competitiveness. Due to the novelty of the technology, whereby many companies are still exploring potential use cases, and considering the complexity of blockchain technology, which may require huge changes to a company’s existing systems and processes, it is important for companies… More >

  • Open Access

    ARTICLE

    On Fractional Differential Inclusion for an Epidemic Model via L-Fuzzy Fixed Point Results

    Maha Noorwali1, Mohammed Shehu Shagari2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1937-1956, 2023, DOI:10.32604/cmes.2023.028239 - 26 June 2023

    Abstract The real world is filled with uncertainty, vagueness, and imprecision. The concepts we meet in everyday life are vague rather than precise. In real-world situations, if a model requires that conclusions drawn from it have some bearings on reality, then two major problems immediately arise, viz. real situations are not usually crisp and deterministic; complete descriptions of real systems often require more comprehensive data than human beings could recognize simultaneously, process and understand. Conventional mathematical tools which require all inferences to be exact, are not always efficient to handle imprecisions in a wide variety of… More >

  • Open Access

    ARTICLE

    Multi-Attribute Group Decision-Making Method under Spherical Fuzzy Bipolar Soft Expert Framework with Its Application

    Mohammed M. Ali Al-Shamiri1,2, Ghous Ali3,*, Muhammad Zain Ul Abidin3, Arooj Adeel3

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1891-1936, 2023, DOI:10.32604/cmes.2023.027844 - 26 June 2023

    Abstract Spherical fuzzy soft expert set (SFSES) theory blends the perks of spherical fuzzy sets and group decision-making into a unified approach. It allows solutions to highly complicated uncertainties and ambiguities under the unbiased supervision and group decision-making of multiple experts. However, SFSES theory has some deficiencies such as the inability to interpret and portray the bipolarity of decision-parameters. This work highlights and overcomes these limitations by introducing the novel spherical fuzzy bipolar soft expert sets (SFBSESs) as a powerful hybridization of spherical fuzzy set theory with bipolar soft expert sets (BSESs). Followed by the development More > Graphic Abstract

    Multi-Attribute Group Decision-Making Method under Spherical Fuzzy Bipolar Soft Expert Framework with Its Application

  • Open Access

    ARTICLE

    New Configurations of the Fuzzy Fractional Differential Boussinesq Model with Application in Ocean Engineering and Their Analysis in Statistical Theory

    Yu-Ming Chu1, Saima Rashid2,*, Shazia Karim3, Anam Sultan2

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1573-1611, 2023, DOI:10.32604/cmes.2023.027724 - 26 June 2023

    Abstract The fractional-order Boussinesq equations (FBSQe) are investigated in this work to see if they can effectively improve the situation where the shallow water equation cannot directly handle the dispersion wave. The fuzzy forms of analytical FBSQe solutions are first derived using the Adomian decomposition method. It also occurs on the sea floor as opposed to at the functionality. A set of dynamical partial differential equations (PDEs) in this article exemplify an unconfined aquifer flow implication. This methodology can accurately simulate climatological intrinsic waves, so the ripples are spread across a large demographic zone. The Aboodh… More >

  • Open Access

    ARTICLE

    Two-Sided Matching Decision Making with Multi-Attribute Probabilistic Hesitant Fuzzy Sets

    Peichen Zhao1, Qi Yue2,*, Zhibin Deng3

    Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 849-873, 2023, DOI:10.32604/iasc.2023.037090 - 29 April 2023

    Abstract In previous research on two-sided matching (TSM) decision, agents’ preferences were often given in the form of exact values of ordinal numbers and linguistic phrase term sets. Nowdays, the matching agent cannot perform the exact evaluation in the TSM situations due to the great fuzziness of human thought and the complexity of reality. Probability hesitant fuzzy sets, however, have grown in popularity due to their advantages in communicating complex information. Therefore, this paper develops a TSM decision-making approach with multi-attribute probability hesitant fuzzy sets and unknown attribute weight information. The agent attribute weight vector should… More >

  • Open Access

    ARTICLE

    Fermatean Hesitant Fuzzy Prioritized Heronian Mean Operator and Its Application in Multi-Attribute Decision Making

    Chuan-Yang Ruan1,2, Xiang-Jing Chen1, Li-Na Han3,*

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3203-3222, 2023, DOI:10.32604/cmc.2023.035480 - 31 March 2023

    Abstract In real life, incomplete information, inaccurate data, and the preferences of decision-makers during qualitative judgment would impact the process of decision-making. As a technical instrument that can successfully handle uncertain information, Fermatean fuzzy sets have recently been used to solve the multi-attribute decision-making (MADM) problems. This paper proposes a Fermatean hesitant fuzzy information aggregation method to address the problem of fusion where the membership, non-membership, and priority are considered simultaneously. Combining the Fermatean hesitant fuzzy sets with Heronian Mean operators, this paper proposes the Fermatean hesitant fuzzy Heronian mean (FHFHM) operator and the Fermatean hesitant… More >

  • Open Access

    ARTICLE

    A New Kind of Generalized Pythagorean Fuzzy Soft Set and Its Application in Decision-Making

    Xiaoyan Wang1, Ahmed Mostafa Khalil2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2861-2871, 2023, DOI:10.32604/cmes.2023.026021 - 09 March 2023

    Abstract The aim of this paper is to introduce the concept of a generalized Pythagorean fuzzy soft set (GPFSS), which is a combination of the generalized fuzzy soft sets and Pythagorean fuzzy sets. Several of important operations of GPFSS including complement, restricted union, and extended intersection are discussed. The basic properties of GPFSS are presented. Further, an algorithm of GPFSSs is given to solve the fuzzy soft decision-making. Finally, a comparative analysis between the GPFSS approach and some existing approaches is provided to show their reliability over them. More >

  • Open Access

    ARTICLE

    Picture-Neutrosophic Trusted Safe Semi-Supervised Fuzzy Clustering for Noisy Data

    Pham Huy Thong1,2,3, Florentin Smarandache4, Phung The Huan5, Tran Manh Tuan6, Tran Thi Ngan6,*, Vu Duc Thai5, Nguyen Long Giang2, Le Hoang Son3

    Computer Systems Science and Engineering, Vol.46, No.2, pp. 1981-1997, 2023, DOI:10.32604/csse.2023.035692 - 09 February 2023

    Abstract Clustering is a crucial method for deciphering data structure and producing new information. Due to its significance in revealing fundamental connections between the human brain and events, it is essential to utilize clustering for cognitive research. Dealing with noisy data caused by inaccurate synthesis from several sources or misleading data production processes is one of the most intriguing clustering difficulties. Noisy data can lead to incorrect object recognition and inference. This 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… More >

  • Open Access

    ARTICLE

    Novel Decision Making Methodology under Pythagorean Probabilistic Hesitant Fuzzy Einstein Aggregation Information

    Shahzaib Ashraf1, Bushra Batool2, Muhammad Naeem3,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 1785-1811, 2023, DOI:10.32604/cmes.2023.024851 - 06 February 2023

    Abstract This research proposes multicriteria decision-making (MCDM)-based real-time Mesenchymal stem cells (MSC) transfusion framework. The testing phase of the methodology denotes the ability to stick to plastic surfaces, the upregulation and downregulation of certain surface protein markers, and lastly, the ability to differentiate into various cell types. First, two scenarios of an enhanced dataset based on a medical perspective were created in the development phase to produce varying levels of emergency. Second, for real-time monitoring of COVID-19 patients with different emergency levels (i.e., mild, moderate, severe, and critical), an automated triage algorithm based on a formal… More >

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