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  • Open Access


    Decision Making Based on Valued Fuzzy Superhypergraphs

    Mohammad Hamidi1,*, Florentin Smarandache2, Mohadeseh Taghinezhad1

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1907-1923, 2024, DOI:10.32604/cmes.2023.030284

    Abstract This paper explores the defects in fuzzy (hyper) graphs (as complex (hyper) networks) and extends the fuzzy (hyper) graphs to fuzzy (quasi) superhypergraphs as a new concept. We have modeled the fuzzy superhypergraphs as complex superhypernetworks in order to make a relation between labeled objects in the form of details and generalities. Indeed, the structure of fuzzy (quasi) superhypergraphs collects groups of labeled objects and analyzes them in the form of the part to part of objects, the part of objects to the whole group of objects, and the whole to the whole group of objects at the same time.… More >

  • Open Access


    A Large-Scale Group Decision Making Model Based on Trust Relationship and Social Network Updating

    Rongrong Ren1,2, Luyang Su1,2, Xinyu Meng1,2, Jianfang Wang3, Meng Zhao1,2,4,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.1, pp. 429-458, 2024, DOI:10.32604/cmes.2023.027310

    Abstract With the development of big data and social computing, large-scale group decision making (LGDM) is now merging with social networks. Using social network analysis (SNA), this study proposes an LGDM consensus model that considers the trust relationship among decision makers (DMs). In the process of consensus measurement: the social network is constructed according to the social relationship among DMs, and the Louvain method is introduced to classify social networks to form subgroups. In this study, the weights of each decision maker and each subgroup are computed by comprehensive network weights and trust weights. In the process of consensus improvement: A… More >

  • Open Access


    Pythagorean Fuzzy Einstein Aggregation Operators with Z-Numbers: Application in Complex Decision Aid Systems

    Shahzad Noor Abbasi1, Shahzaib Ashraf1,*, M. Shazib Hameed1, Sayed M. Eldin2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.3, pp. 2795-2844, 2023, DOI:10.32604/cmes.2023.028963

    Abstract The primary goal of this research is to determine the optimal agricultural field selection that would most effectively support manufacturing producers in manufacturing production while accounting for unpredictability and reliability in their decision-making. The PFS is known to address the levels of participation and non-participation. To begin, we introduce the novel concept of a PFZN, which is a hybrid structure of Pythagorean fuzzy sets and the ZN. The PFZN is graded in terms of membership and non-membership, as well as reliability, which provides a strong advice in real-world decision support concerns. The PFZN is a useful tool for dealing with… More >

  • Open Access


    Investigation of the Severity of Modular Construction Adoption Barriers with Large-Scale Group Decision Making in an Organization from Internal and External Stakeholder Perspectives

    Muzi Li*

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.3, pp. 2465-2493, 2023, DOI:10.32604/cmes.2023.026827

    Abstract Modular construction as an innovative method aids the construction industry in transforming to off-site construction production with high efficiency and environmental friendliness. Despite the obvious advantages, the uptake of modular construction is not booming as expected. However, previous studies have investigated and summarized the barriers to the adoption of modular construction. In this research, a Large-Scale Group Decision Making (LSGDM)- based analysis is first made of the severity of barriers to modular construction adoption from the perspective of construction stakeholders. In addition, the Technology-Organization-Environment (TOE) framework is utilized to identify the barriers based on three contexts (technology, organization, and environment).… More >

  • 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


    High Utility Periodic Frequent Pattern Mining in Multiple Sequences

    Chien-Ming Chen1, Zhenzhou Zhang1, Jimmy Ming-Tai Wu1, Kuruva Lakshmanna2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 733-759, 2023, DOI:10.32604/cmes.2023.027463

    Abstract Periodic pattern mining has become a popular research subject in recent years; this approach involves the discovery of frequently recurring patterns in a transaction sequence. However, previous algorithms for periodic pattern mining have ignored the utility (profit, value) of patterns. Additionally, these algorithms only identify periodic patterns in a single sequence. However, identifying patterns of high utility that are common to a set of sequences is more valuable. In several fields, identifying high-utility periodic frequent patterns in multiple sequences is important. In this study, an efficient algorithm called MHUPFPS was proposed to identify such patterns. To address existing problems, three… More >

  • Open Access


    Intelligent Beetle Antenna Search with Deep Transfer Learning Enabled Medical Image Classification Model

    Mohamed Ibrahim Waly*

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 3159-3174, 2023, DOI:10.32604/csse.2023.035900

    Abstract Recently, computer assisted diagnosis (CAD) model creation has become more dependent on medical picture categorization. It is often used to identify several conditions, including brain disorders, diabetic retinopathy, and skin cancer. Most traditional CAD methods relied on textures, colours, and forms. Because many models are issue-oriented, they need a more substantial capacity to generalize and cannot capture high-level problem domain notions. Recent deep learning (DL) models have been published, providing a practical way to develop models specifically for classifying input medical pictures. This paper offers an intelligent beetle antenna search (IBAS-DTL) method for classifying medical images facilitated by deep transfer… More >

  • Open Access


    Heap Based Optimization with Deep Quantum Neural Network Based Decision Making on Smart Healthcare Applications

    Iyad Katib1, Mahmoud Ragab2,*

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 3749-3765, 2023, DOI:10.32604/csse.2023.036796

    Abstract The concept of smart healthcare has seen a gradual increase with the expansion of information technology. Smart healthcare will use a new generation of information technologies, like artificial intelligence, the Internet of Things (IoT), cloud computing, and big data, to transform the conventional medical system in an all-around way, making healthcare highly effective, more personalized, and more convenient. This work designs a new Heap Based Optimization with Deep Quantum Neural Network (HBO-DQNN) model for decision-making in smart healthcare applications. The presented HBO-DQNN model majorly focuses on identifying and classifying healthcare data. In the presented HBO-DQNN model, three stages of operations… 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 >

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