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  • Open Access

    ARTICLE

    Novel Distance Measures on Hesitant Fuzzy Sets Based on Equal-Probability Transformation and Their Application in Decision Making on Intersection Traffic Control

    Fangwei Zhang1,2, Yi Zhao3,*, Jun Ye4, Shuhong Wang5, Jingyi Hu6

    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.2, pp. 1589-1602, 2023, DOI:10.32604/cmes.2022.022431 - 27 October 2022

    Abstract The purpose of this study is to reduce the uncertainty in the calculation process on hesitant fuzzy sets (HFSs). The innovation of this study is to unify the cardinal numbers of hesitant fuzzy elements (HFEs) in a special way. Firstly, a probability density function is assigned for any given HFE. Thereafter, equal-probability transformation is introduced to transform HFEs with different cardinal numbers on the condition into the same probability density function. The characteristic of this transformation is that the higher the consistency of the membership degrees in HFEs, the higher the credibility of the mentioned More >

  • Open Access

    ARTICLE

    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 - 20 September 2022

    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 More >

  • Open Access

    ARTICLE

    Encephalitis Detection from EEG Fuzzy Density-Based Clustering Model with Multiple Centroid

    Hanan Abdullah Mengash1, Alaaeldin M. Hafez2, Hanan A. Hosni Mahmoud3,*

    Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3129-3140, 2023, DOI:10.32604/iasc.2023.030836 - 17 August 2022

    Abstract Encephalitis is a brain inflammation disease. Encephalitis can yield to seizures, motor disability, or some loss of vision or hearing. Sometimes, encephalitis can be a life-threatening and proper diagnosis in an early stage is very crucial. Therefore, in this paper, we are proposing a deep learning model for computerized detection of Encephalitis from the electroencephalogram data (EEG). Also, we propose a Density-Based Clustering model to classify the distinctive waves of Encephalitis. Customary clustering models usually employ a computed single centroid virtual point to define the cluster configuration, but this single point does not contain adequate More >

  • Open Access

    ARTICLE

    Selection of Wind Turbine Systems for the Sultanate of Oman

    M. A. A. Younis1,*, Anas Quteishat1,2

    Computer Systems Science and Engineering, Vol.45, No.1, pp. 343-359, 2023, DOI:10.32604/csse.2023.029510 - 16 August 2022

    Abstract The Sultanate of Oman has been dealing with a severe renewable energy issue for the past few decades, and the government has struggled to find a solution. In addition, Oman’s strategy for converting power generation to sources of renewable energy includes a goal of 60 percent of national energy demands being met by renewables by 2040, including solar and wind turbines. Furthermore, the use of small-scale energy from wind devices has been on the rise in recent years. This upward trend is attributed to advancements in wind turbine technology, which have lowered the cost of… More >

  • Open Access

    ARTICLE

    Multi-attribute Group Decision-making Based on Hesitant Bipolar-valued Fuzzy Information and Social Network

    Dhanalakshmi R1, Sovan Samanta2, Arun Kumar Sivaraman3, Jeong Gon Lee4,*, Balasundaram A5, Sanamdikar Sanjay Tanaji6, Priya Ravindran7

    Computer Systems Science and Engineering, Vol.44, No.3, pp. 1939-1950, 2023, DOI:10.32604/csse.2023.026254 - 01 August 2022

    Abstract Fuzzy sets have undergone several expansions and generalisations in the literature, including Atanasov’s intuitionistic fuzzy sets, type 2 fuzzy sets, and fuzzy multisets, to name a few. They can be regarded as fuzzy multisets from a formal standpoint; nevertheless, their interpretation differs from the two other approaches to fuzzy multisets that are currently available. Hesitating fuzzy sets (HFS) are very useful if consultants have hesitation in dealing with group decision-making problems between several possible memberships. However, these possible memberships can be not only crisp values in [0,1], but also interval values during a practical evaluation… More >

  • Open Access

    ARTICLE

    Strategic Renewable Energy Resource Selection Using a Fuzzy Decision-Making Method

    Anas Quteishat1,2,*, M. A. A. Younis2

    Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 2117-2134, 2023, DOI:10.32604/iasc.2023.029419 - 19 July 2022

    Abstract Renewable energy is created by renewable natural resources such as geothermal heat, sunlight, tides, rain, and wind. Energy resources are vital for all countries in terms of their economies and politics. As a result, selecting the optimal option for any country is critical in terms of energy investments. Every country is nowadays planning to increase the share of renewable energy in their universal energy sources as a result of global warming. In the present work, the authors suggest fuzzy multi-characteristic decision-making approaches for renewable energy source selection, and fuzzy set theory is a valuable methodology More >

  • Open Access

    ARTICLE

    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 - 28 July 2022

    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 More >

  • Open Access

    ARTICLE

    A Unified Decision-Making Technique for Analysing Treatments in Pandemic Context

    Fawaz Alsolami1, Abdullah Saad Al-Malaise Alghamdi2, Asif Irshad Khan1,*, Yoosef B. Abushark1, Abdulmohsen Almalawi1, Farrukh Saleem2, Alka Agrawal3, Rajeev Kumar4, Raees Ahmad Khan3

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 2591-2618, 2022, DOI:10.32604/cmc.2022.025703 - 16 June 2022

    Abstract The COVID-19 pandemic has triggered a global humanitarian disaster that has never been seen before. Medical experts, on the other hand, are undecided on the most valuable treatments of therapy because people ill with this infection exhibit a wide range of illness indications at different phases of infection. Further, this project aims to undertake an experimental investigation to determine which treatments for COVID-19 disease is the most effective and preferable. The research analysis is based on vast data gathered from professionals and research journals, making this study a comprehensive reference. To solve this challenging task,… 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 - 29 March 2022

    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… More >

  • Open Access

    ARTICLE

    Fusion of Infrared and Visible Images Using Fuzzy Based Siamese Convolutional Network

    Kanika Bhalla1, Deepika Koundal2,*, Surbhi Bhatia3, Mohammad Khalid Imam Rahmani4, Muhammad Tahir4

    CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5503-5518, 2022, DOI:10.32604/cmc.2022.021125 - 11 October 2021

    Abstract Traditional techniques based on image fusion are arduous in integrating complementary or heterogeneous infrared (IR)/visible (VS) images. Dissimilarities in various kind of features in these images are vital to preserve in the single fused image. Hence, simultaneous preservation of both the aspects at the same time is a challenging task. However, most of the existing methods utilize the manual extraction of features; and manual complicated designing of fusion rules resulted in a blurry artifact in the fused image. Therefore, this study has proposed a hybrid algorithm for the integration of multi-features among two heterogeneous images.… More >

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