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  • Open Access

    ARTICLE

    Dombi-Normalized Weighted Bonferroni Mean Operators with Novel Multiple-Valued Complex Neutrosophic Uncertain Linguistic Sets and Their Application in Decision Making

    Tahir Mahmood1, Zeeshan Ali1, Dulyawit Prangchumpol2,*, Thammarat Panityakul3

    CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.3, pp. 1587-1623, 2022, DOI:10.32604/cmes.2022.017998 - 30 December 2021

    Abstract Although fuzzy set concepts have evolved, neutrosophic sets are attracting more attention due to the greater power of the structure of neutrosophic sets. The ability to account for components that are true, false or neither true nor false is useful in the resolution of real-life problems. However, simultaneous variations render neutrosophic sets unsuitable in specific circumstances. To enable the management of these sorts of issues, we combine the principle of multi-valued neutrosophic uncertain linguistic sets and complex fuzzy sets to develop the principle of multi-valued complex neutrosophic uncertain linguistic sets. Multi-valued complex neutrosophic uncertain linguistic… More >

  • Open Access

    ARTICLE

    Sine Trigonometry Operational Laws for Complex Neutrosophic Sets and Their Aggregation Operators in Material Selection

    D. Ajay1, J. Aldring1, G. Rajchakit2, P. Hammachukiattikul3, N. Boonsatit4,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.2, pp. 1033-1076, 2022, DOI:10.32604/cmes.2022.018267 - 13 December 2021

    Abstract In this paper, sine trigonometry operational laws (ST-OLs) have been extended to neutrosophic sets (NSs) and the operations and functionality of these laws are studied. Then, extending these ST-OLs to complex neutrosophic sets (CNSs) forms the core of this work. Some of the mathematical properties are proved based on ST-OLs. Fundamental operations and the distance measures between complex neutrosophic numbers (CNNs) based on the ST-OLs are discussed with numerical illustrations. Further the arithmetic and geometric aggregation operators are established and their properties are verified with numerical data. The general properties of the developed sine trigonometry… More >

  • Open Access

    ARTICLE

    Automated Deep Learning Based Cardiovascular Disease Diagnosis Using ECG Signals

    S. Karthik1, M. Santhosh1,*, M. S. Kavitha1, A. Christopher Paul2

    Computer Systems Science and Engineering, Vol.42, No.1, pp. 183-199, 2022, DOI:10.32604/csse.2022.021698 - 02 December 2021

    Abstract Automated biomedical signal processing becomes an essential process to determine the indicators of diseased states. At the same time, latest developments of artificial intelligence (AI) techniques have the ability to manage and analyzing massive amounts of biomedical datasets results in clinical decisions and real time applications. They can be employed for medical imaging; however, the 1D biomedical signal recognition process is still needing to be improved. Electrocardiogram (ECG) is one of the widely used 1-dimensional biomedical signals, which is used to diagnose cardiovascular diseases. Computer assisted diagnostic models find it difficult to automatically classify the… More >

  • Open Access

    ARTICLE

    Decision-Making Problems under the Environment of m-Polar Diophantine Neutrosophic N-Soft Set

    Shouzhen Zeng1,2, Shahbaz Ali3,*, Muhammad Khalid Mahmood4, Florentin Smarandache5, Daud Ahmad4

    CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.1, pp. 581-606, 2022, DOI:10.32604/cmes.2022.017397 - 29 November 2021

    Abstract Fuzzy models are present everywhere from natural to artificial structures, embodying the dynamic processes in physical, biological, and social systems. As real-life problems are often uncertain on account of inconsistent and indeterminate information, it seems very demanding for an expert to solve those problems using a fuzzy model. In this regard, we develop a hybrid new model m-polar Diophantine neutrosophic N-soft set which is based on neutrosophic set and soft set. Additionally, we define several different sorts of compliments on the proposed set. A proposed set is a generalized form of fuzzy, soft, Pythagorean fuzzy, More >

  • Open Access

    ARTICLE

    Coronavirus Decision-Making Based on a Locally -Generalized Closed Set

    M. A. El Safty1,*, S. A. Alblowi2, Yahya Almalki3, M. El Sayed4

    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 483-498, 2022, DOI:10.32604/iasc.2022.021581 - 26 October 2021

    Abstract Real-world applications now deal with a massive amount of data, and information about the world is inaccurate, incomplete, or uncertain. Therefore, we present in our paper a proposed model for solving problems. This model is based on the class of locally generalized closed sets, namely, locally simply* alpha generalized closed* sets and locally simply* alpha generalized closed** sets (briefly, -sets and -sets), based on simply* alpha open set. We also introduce various concepts of their properties and their relationship with other types, and we are studying several of their properties. Finally, we apply the concept More >

  • Open Access

    ARTICLE

    Intelligent Integrated Model for Improving Performance in Power Plants

    Ahmed Ali Ajmi1,2, Noor Shakir Mahmood1,2, Khairur Rijal Jamaludin1,*, Hayati Habibah Abdul Talib1, Shamsul Sarip1, Hazilah Mad Kaidi1

    CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5783-5801, 2022, DOI:10.32604/cmc.2022.021885 - 11 October 2021

    Abstract Industry 4.0 is expected to play a crucial role in improving energy management and personnel performance in power plants. Poor performance problem in maintaining power plants is the result of both human errors, human factors and the poor implementation of automation in energy management. This problem can potentially be solved using artificial intelligence (AI) and an integrated management system (IMS). This article investigates the current challenges to improving personnel and energy management performance in power plants, identifies the critical success factors (CSFs) for an integrated intelligent framework, and develops an intelligent framework that enables power… More >

  • Open Access

    ARTICLE

    Artificial Intelligence Based Optimal Functional Link Neural Network for Financial Data Science

    Anwer Mustafa Hilal1, Hadeel Alsolai2, Fahd N. Al-Wesabi3, Mohammed Abdullah Al-Hagery4, Manar Ahmed Hamza1,*, Mesfer Al Duhayyim5

    CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 6289-6304, 2022, DOI:10.32604/cmc.2022.021522 - 11 October 2021

    Abstract In present digital era, data science techniques exploit artificial intelligence (AI) techniques who start and run small and medium-sized enterprises (SMEs) to have an impact and develop their businesses. Data science integrates the conventions of econometrics with the technological elements of data science. It make use of machine learning (ML), predictive and prescriptive analytics to effectively understand financial data and solve related problems. Smart technologies for SMEs enable allows the firm to get smarter with their processes and offers efficient operations. At the same time, it is needed to develop an effective tool which can… More >

  • Open Access

    ARTICLE

    Machine Learning Based Depression, Anxiety, and Stress Predictive Model During COVID-19 Crisis

    Fahd N. Al-Wesabi1,2,*, Hadeel Alsolai3, Anwer Mustafa Hilal4, Manar Ahmed Hamza4, Mesfer Al Duhayyim5, Noha Negm6,7

    CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5803-5820, 2022, DOI:10.32604/cmc.2022.021195 - 11 October 2021

    Abstract Corona Virus Disease-2019 (COVID-19) was reported at first in Wuhan city, China by December 2019. World Health Organization (WHO) declared COVID-19 as a pandemic i.e., global health crisis on March 11, 2020. The outbreak of COVID-19 pandemic and subsequent lockdowns to curb the spread, not only affected the economic status of a number of countries, but it also resulted in increased levels of Depression, Anxiety, and Stress (DAS) among people. Therefore, there is a need exists to comprehend the relationship among psycho-social factors in a country that is hypothetically affected by high levels of stress and… More >

  • Open Access

    ARTICLE

    A Fuzzy MCDM Model of Supplier Selection in Supply Chain Management

    Jui-Chung Kao1, Chia-Nan Wang2,*, Viet Tinh Nguyen3 and Syed Tam Husain3

    Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1451-1466, 2022, DOI:10.32604/iasc.2022.021778 - 09 October 2021

    Abstract According to a new study by the International Labor Organization (ILO), the COVID-19 pandemic has had a strong impact on the garment industry in the Asia-Pacific region. A sharp drop in retail sales in key export markets has affected workers and businesses across supply chains. To ensure the effectiveness and efficiency of garment supply chain, choosing a sustainable supplier should be a main concern of all businesses. The supplier selection problem in garment industry involves multiple quantitative and qualitative criteria. There have been many research and literatures about the development and application of Multicriteria Decision… More >

  • Open Access

    ARTICLE

    Database Recovery Technique for Mobile Computing: A Game Theory Approach

    Magda M. Madbouly1, Yasser F. Mokhtar2, Saad M. Darwish1,*

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3205-3219, 2022, DOI:10.32604/cmc.2022.019440 - 27 September 2021

    Abstract Contact between mobile hosts and database servers presents many problems in the Mobile Database System (MDS). It is harmed by a variety of causes, including handoff, inadequate capacity, frequent transaction updates, and repeated failures, both of which contribute to serious issues with the information system’s consistency. However, error tolerance technicality allows devices to continue performing their functions in the event of a failure. The aim of this paper is to identify the optimal recovery approach from among the available state-of-the-art techniques in MDS by employing game theory. Several of the presented recovery protocols are chosen More >

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