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  • Open Access

    ARTICLE

    Complex Decision Modeling Framework with Fairly Operators and Quaternion Numbers under Intuitionistic Fuzzy Rough Context

    Nadeem Salamat1, Muhammad Kamran1,2,*, Shahzaib Ashraf1, Manal Elzain Mohammed Abdulla3, Rashad Ismail3, Mohammed M. Al-Shamiri3

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1893-1933, 2024, DOI:10.32604/cmes.2023.044697

    Abstract The main goal of informal computing is to overcome the limitations of hypersensitivity to defects and uncertainty while maintaining a balance between high accuracy, accessibility, and cost-effectiveness. This paper investigates the potential applications of intuitionistic fuzzy sets (IFS) with rough sets in the context of sparse data. When it comes to capture uncertain information emanating from both upper and lower approximations, these intuitionistic fuzzy rough numbers (IFRNs) are superior to intuitionistic fuzzy sets and pythagorean fuzzy sets, respectively. We use rough sets in conjunction with IFSs to develop several fairly aggregation operators and analyze their underlying properties. We present numerous… More > Graphic Abstract

    Complex Decision Modeling Framework with Fairly Operators and Quaternion Numbers under Intuitionistic Fuzzy Rough Context

  • 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

    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 effectively with noisy decision tables,… 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

    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 to carefully evaluate suitable use… More >

  • Open Access

    ARTICLE

    Selecting Best Software Vulnerability Scanner Using Intuitionistic Fuzzy Set TOPSIS

    Navneet Bhatt1, Jasmine Kaur2, Adarsh Anand2, Omar H. Alhazmi3,*

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3613-3629, 2022, DOI:10.32604/cmc.2022.026554

    Abstract Software developers endeavor to build their products with the least number of bugs. Despite this, many vulnerabilities are detected in software that threatens its integrity. Various automated software i.e., vulnerability scanners, are available in the market which helps detect and manage vulnerabilities in a computer, application, or a network. Hence, the choice of an appropriate vulnerability scanner is crucial to ensure efficient vulnerability management. The current work serves a dual purpose, first, to identify the key factors which affect the vulnerability discovery process in a network. The second, is to rank the popular vulnerability scanners based on the identified attributes.… More >

  • Open Access

    ARTICLE

    Power Aggregation Operators and Similarity Measures Based on Improved Intuitionistic Hesitant Fuzzy Sets and their Applications to Multiple Attribute Decision Making

    Tahir Mahmood1, Wajid Ali1, Zeeshan Ali1, Ronnason Chinram2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.126, No.3, pp. 1165-1187, 2021, DOI:10.32604/cmes.2021.014393

    Abstract Intuitionistic hesitant fuzzy set (IHFS) is a mixture of two separated notions called intuitionistic fuzzy set (IFS) and hesitant fuzzy set (HFS), as an important technique to cope with uncertain and awkward information in realistic decision issues. IHFS contains the grades of truth and falsity in the form of the subset of the unit interval. The notion of IHFS was defined by many scholars with different conditions, which contain several weaknesses. Here, keeping in view the problems of already defined IHFSs, we will define IHFS in another way so that it becomes compatible with other existing notions. To examine the… More >

  • Open Access

    ARTICLE

    Intuitionistic Fuzzy Petri Nets Model Based on Back Propagation Algorithm for Information Services

    Junhua Xi1, *, Kouquan Zheng1, Jianfeng Ma1, Jungang Yang1, Zhiyao Liang2

    CMC-Computers, Materials & Continua, Vol.63, No.2, pp. 605-619, 2020, DOI:10.32604/cmc.2020.06343

    Abstract Intuitionistic fuzzy Petri net is an important class of Petri nets, which can be used to model the knowledge base system based on intuitionistic fuzzy production rules. In order to solve the problem of poor self-learning ability of intuitionistic fuzzy systems, a new Petri net modeling method is proposed by introducing BP (Error Back Propagation) algorithm in neural networks. By judging whether the transition is ignited by continuous function, the intuitionistic fuzziness of classical BP algorithm is extended to the parameter learning and training, which makes Petri network have stronger generalization ability and adaptive function, and the reasoning result is… More >

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