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  • Open Access


    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

    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 be obtained by using the… More >

  • Open Access


    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

    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 fuzzy weighted Heronian mean (FHFWHM)… More >

  • Open Access


    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

    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


    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

    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 using neutral and refusal degrees… More >

  • Open Access


    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

    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 medical guideline is proposed, taking… More >

  • Open Access


    An Edge Computing Algorithm Based on Multi-Level Star Sensor Cloud

    Siyu Ren1, Shi Qiu2,*, Keyang Cheng3

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 1643-1659, 2023, DOI:10.32604/cmes.2023.025248

    Abstract Star sensors are an important means of autonomous navigation and access to space information for satellites. They have been widely deployed in the aerospace field. To satisfy the requirements for high resolution, timeliness, and confidentiality of star images, we propose an edge computing algorithm based on the star sensor cloud. Multiple sensors cooperate with each other to form a sensor cloud, which in turn extends the performance of a single sensor. The research on the data obtained by the star sensor has very important research and application values. First, a star point extraction model is proposed based on the fuzzy… More >

  • Open Access


    Novel Scheme for Robust Confusion Component Selection Based on Pythagorean Fuzzy Set

    Nabilah Abughazalah1, Mohsin Iqbal2, Majid Khan3,*, Iqtadar Hussain4,5

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6523-6534, 2023, DOI:10.32604/cmc.2022.031859

    Abstract The substitution box, often known as an S-box, is a nonlinear component that is a part of several block ciphers. Its purpose is to protect cryptographic algorithms from a variety of cryptanalytic assaults. A MultiCriteria Decision Making (MCDM) problem has a complex selection procedure because of having many options and criteria to choose from. Because of this, statistical methods are necessary to assess the performance score of each S-box and decide which option is the best one available based on this score. Using the Pythagorean Fuzzy-based Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method, the major… More >

  • Open Access


    Comparative Analysis of Pythagorean MCDM Methods for the Risk Assessment of Childhood Cancer

    Shaista Habib1, Muhammad Akram2,*, M. M. Ali Al-Shamiri3

    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.3, pp. 2585-2615, 2023, DOI:10.32604/cmes.2023.024551

    Abstract According to the World Health Organization (WHO), cancer is the leading cause of death for children in low and middle-income countries. Around 400,000 kids get diagnosed with this illness each year, and their survival rate depends on the country in which they live. In this article, we present a Pythagorean fuzzy model that may help doctors identify the most likely type of cancer in children at an early stage by taking into account the symptoms of different types of cancer. The Pythagorean fuzzy decision-making techniques that we utilize are Pythagorean Fuzzy TOPSIS, Pythagorean Fuzzy Entropy (PF-Entropy), and Pythagorean Fuzzy Power… More > Graphic Abstract

    Comparative Analysis of Pythagorean MCDM Methods for the Risk Assessment of Childhood Cancer

  • Open Access


    (α, γ)-Anti-Multi-Fuzzy Subgroups and Some of Its Properties

    Memet Şahin1, Vakkas Uluçay2, S. A. Edalatpanah3,*, Fayza Abdel Aziz Elsebaee4, Hamiden Abd El-Wahed Khalifa5

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3221-3229, 2023, DOI:10.32604/cmc.2023.033006

    Abstract Recently, fuzzy multi-sets have come to the forefront of scientists’ interest and have been used in algebraic structures such as multi-groups, multi-rings, anti-fuzzy multigroup and (α, γ)-anti-fuzzy subgroups. In this paper, we first summarize the knowledge about the algebraic structure of fuzzy multi-sets such as (α, γ)-anti-multi-fuzzy subgroups. In a way, the notion of anti-fuzzy multigroup is an application of anti-fuzzy multi sets to the theory of group. The concept of anti-fuzzy multigroup is a complement of an algebraic structure of a fuzzy multi set that generalizes both the theories of classical group and fuzzy group. The aim of this… More >

  • Open Access


    A Grey Simulation-Based Fuzzy Hierarchical Approach for Diagnosing Healthcare Service Quality

    Phi-Hung Nguyen*, Hong-Anh Pham

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3231-3248, 2023, DOI:10.32604/cmc.2023.031428

    Abstract This study aims to assess and rank the service quality of the healthcare system utilizing a Fuzzy Analytical Hierarchical Process (Fuzzy AHP) and Grey Relational Analysis (Fuzzy GRA) technique. In this study, the six primary characteristics of healthcare service quality, comprising Tangibles (A), Healthcare Staff (B), Responsiveness (C), Relationships (D), Support Service (E), and Accessibility (F), are examined through a case study of 20 private and public hospitals in Hanoi, Vietnam. The weighting results of Fuzzy AHP technique indicated that Responsiveness (C) has the highest ranking, followed by Relationships (D) and Healthcare Staff (B). Meanwhile, Tangibility has finally comprised the… More >

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