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  • Open Access


    Pythagorean Neutrosophic Planar Graphs with an Application in Decision-Making

    P. Chellamani1,2,*, D. Ajay1, Mohammed M. Al-Shamiri3,4, Rashad Ismail3,4

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 4935-4953, 2023, DOI:10.32604/cmc.2023.036321

    Abstract Graph theory has a significant impact and is crucial in the structure of many real-life situations. To simulate uncertainty and ambiguity, many extensions of graph theoretical notions were created. Planar graphs play a vital role in modelling which has the property of non-crossing edges. Although crossing edges benefit, they have some drawbacks, which paved the way for the introduction of planar graphs. The overall purpose of the study is to contribute to the conceptual development of the Pythagorean Neutrosophic graph. The basic methodology of our research is the incorporation of the analogous concepts of planar graphs in the Pythagorean Neutrosophic… 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


    Emerging Trends in Social Networking Systems and Generation Gap with Neutrosophic Crisp Soft Mapping

    Muhammad Riaz1, Masooma Raza Hashmi1, Faruk Karaaslan2, Aslıhan Sezgin3, Mohammed M. Ali Al Shamiri4,5,*, Mohammed M. Khalaf6,7

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 1759-1783, 2023, DOI:10.32604/cmes.2023.023327

    Abstract This paper aims to introduce the novel concept of neutrosophic crisp soft set (NCSS), including various types of neutrosophic crisp soft sets (NCSSs) and their fundamental operations. We define NCS-mapping and its inverse NCS-mapping between two NCS-classes. We develop a robust mathematical modeling with the help of NCS-mapping to analyze the emerging trends in social networking systems (SNSs) for our various generations. We investigate the advantages, disadvantages, and natural aspects of SNSs for five generations. With the changing of the generations, it is analyzed that emerging trends and the benefits of SNSs are increasing day by day. The suggested modeling… More > Graphic Abstract

    Emerging Trends in Social Networking Systems and Generation Gap with Neutrosophic Crisp Soft Mapping

  • Open Access


    Type-2 Neutrosophic Set and Their Applications in Medical Databases Deadlock Resolution

    Marwan H. Hassan1, Saad M. Darwish2,*, Saleh M. Elkaffas3

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 4417-4434, 2023, DOI:10.32604/cmc.2023.033175

    Abstract Electronic patient data gives many advantages, but also new difficulties. Deadlocks may delay procedures like acquiring patient information. Distributed deadlock resolution solutions introduce uncertainty due to inaccurate transaction properties. Soft computing-based solutions have been developed to solve this challenge. In a single framework, ambiguous, vague, incomplete, and inconsistent transaction attribute information has received minimal attention. The work presented in this paper employed type-2 neutrosophic logic, an extension of type-1 neutrosophic logic, to handle uncertainty in real-time deadlock-resolving systems. The proposed method is structured to reflect multiple types of knowledge and relations among transactions’ features that include validation factor degree, slackness… More >

  • Open Access


    Proposed Framework for Detection of Breast Tumors

    Mostafa Elbaz1,2,*, Haitham Elwahsh1, Ibrahim Mahmoud El-Henawy2

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2927-2944, 2023, DOI:10.32604/cmc.2023.033111

    Abstract Computer vision is one of the significant trends in computer science. It plays as a vital role in many applications, especially in the medical field. Early detection and segmentation of different tumors is a big challenge in the medical world. The proposed framework uses ultrasound images from Kaggle, applying five diverse models to denoise the images, using the best possible noise-free image as input to the U-Net model for segmentation of the tumor, and then using the Convolution Neural Network (CNN) model to classify whether the tumor is benign, malignant, or normal. The main challenge faced by the framework in… More >

  • Open Access


    Developments and Applications of Neutrosophic Theory in Civil Engineering Fields: A Review

    Zhenhan Zhang, Jun Ye*

    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.2, pp. 887-916, 2023, DOI:10.32604/cmes.2023.022961

    Abstract Neutrosophic theory can effectively and reasonably express indeterminate, inconsistent, and incomplete information. Since Smarandache proposed the neutrosophic theory in 1998, neutrosophic theory and related research have been developed and applied to many important fields. Indeterminacy and fuzziness are one of the main research issues in the field of civil engineering. Therefore, the neutrosophic theory is very suitable for modeling and applications of civil engineering fields. This review paper mainly describes the recent developments and applications of neutrosophic theory in four important research areas of civil engineering: the neutrosophic decision-making theory and applied methods, the neutrosophic evaluation methods and applications of… More >

  • Open Access


    Neutrosophic Adaptive Clustering Optimization in Genetic Algorithm and Its Application in Cubic Assignment Problem

    Fangwei Zhang1,2,*, Shihe Xu3, Bing Han4, Liming Zhang2, Jun Ye5

    CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.3, pp. 2211-2226, 2023, DOI:10.32604/cmes.2022.022418

    Abstract In optimization theory, the adaptive control of the optimization process is an important goal that people pursue. To solve this problem, this study introduces the idea of neutrosophic decision-making into classical heuristic algorithm, and proposes a novel neutrosophic adaptive clustering optimization thought, which is applied in a novel neutrosophic genetic algorithm (NGA), for example. The main feature of NGA is that the NGA treats the crossover effect as a neutrosophic fuzzy set, the variation ratio as a structural parameter, the crossover effect as a benefit parameter and the variation effect as a cost parameter, and then a neutrosophic fitness function… More >

  • Open Access


    Introduction to the Special Issue on Advances in Neutrosophic and Plithogenic Sets for Engineering and Sciences: Theory, Models, and Applications

    S. A. Edalatpanah1,*, Florentin Smarandache2

    CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.2, pp. 817-819, 2023, DOI:10.32604/cmes.2022.024060

    Abstract This article has no abstract. More >

  • Open Access


    Diabetic Retinopathy Diagnosis Using Interval Neutrosophic Segmentation with Deep Learning Model

    V. Thanikachalam1,*, M. G. Kavitha2, V. Sivamurugan1

    Computer Systems Science and Engineering, Vol.44, No.3, pp. 2129-2145, 2023, DOI:10.32604/csse.2023.026527

    Abstract In recent times, Internet of Things (IoT) and Deep Learning (DL) models have revolutionized the diagnostic procedures of Diabetic Retinopathy (DR) in its early stages that can save the patient from vision loss. At the same time, the recent advancements made in Machine Learning (ML) and DL models help in developing Computer Aided Diagnosis (CAD) models for DR recognition and grading. In this background, the current research works designs and develops an IoT-enabled Effective Neutrosophic based Segmentation with Optimal Deep Belief Network (ODBN) model i.e., NS-ODBN model for diagnosis of DR. The presented model involves Interval Neutrosophic Set (INS) technique… More >

  • Open Access


    Bipolar Interval-Valued Neutrosophic Optimization Model of Integrated Healthcare System

    Sumbal Khalil1, Sajida Kousar1, Nasreen Kausar2, Muhammad Imran3, Georgia Irina Oros4,*

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 6207-6224, 2022, DOI:10.32604/cmc.2022.030547

    Abstract Bipolar Interval-valued neutrosophic set is another generalization of fuzzy set, neutrosophic set, bipolar fuzzy set and bipolar neutrosophic set and thus when applied to the optimization problem handles uncertain data more efficiently and flexibly. Current work is an effort to design a flexible optimization model in the backdrop of interval-valued bipolar neutrosophic sets. Bipolar interval-valued neutrosophic membership grades are picked so that they indicate the restriction of the plausible infringement of the inequalities given in the problem. To prove the adequacy and effectiveness of the method a unified system of sustainable medical healthcare supply chain model with an uncertain figure… More >

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