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  • 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

    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

    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

    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

    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

    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 >

  • Open Access

    ARTICLE

    Improving Supply Chain Performance Through Supplier Selection and Order Allocation Problem

    Chia-Nan Wang1, Ming-Cheng Tsou2,*, Chih-Hung Wang3, Viet Tinh Nguyen4, Pham Ngo Thi Phuong5

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1667-1681, 2022, DOI:10.32604/cmc.2022.019833

    Abstract Suppliers play the vital role of ensuring the continuous supply of goods to the market for businesses. If businesses do not maintain a strong bond with their suppliers, they may not be able to secure a steady supply of goods and products for their customers. As a result of failure to deliver products, the production and business activities of the business can be delayed which leads to the loss of customers. Normally, each trading enterprise will have a variety of commodity supply chains with multiple suppliers. Suppliers play an important role and contribute to the… More >

  • Open Access

    ARTICLE

    Hybrid Computational Modeling for Web Application Security Assessment

    Adil Hussain Seh1, Jehad F. Al-Amri2, Ahmad F. Subahi3, Md Tarique Jamal Ansari1, Rajeev Kumar4,*, Mohammad Ubaidullah Bokhari5, Raees Ahmad Khan1

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 469-489, 2022, DOI:10.32604/cmc.2022.019593

    Abstract Transformation from conventional business management systems to smart digital systems is a recurrent trend in the current era. This has led to digital revolution, and in this context, the hardwired technologies in the software industry play a significant role However, from the beginning, software security remains a serious issue for all levels of stakeholders. Software vulnerabilities lead to intrusions that cause data breaches and result in disclosure of sensitive data, compromising the organizations’ reputation that translates into, financial losses as well. Most of the data breaches are financially motivated, especially in the healthcare sector. The… More >

  • Open Access

    ARTICLE

    Medical Waste Treatment Station Selection Based on Linguistic q-Rung Orthopair Fuzzy Numbers

    Jie Ling1,2, Xinmei Li1,2, Mingwei Lin1,2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.1, pp. 117-148, 2021, DOI:10.32604/cmes.2021.016356

    Abstract During the COVID-19 outbreak, the use of single-use medical supplies increased significantly. It is essential to select suitable sites for establishing medical waste treatment stations. It is a big challenge to solve the medical waste treatment station selection problem due to some conflicting factors. This paper proposes a multi-attribute decision-making (MADM) method based on the partitioned Maclaurin symmetric mean (PMSM) operator. For the medical waste treatment station selection problem, the factors or attributes (these two terms can be interchanged.) in the same clusters are closely related, and the attributes in different clusters have no relationships.… More >

  • Open Access

    ARTICLE

    Decision Making Based on Fuzzy Soft Sets and Its Application in COVID-19

    S. A. Al blowi1, M. El Sayed2, M. A. El Safty3,*

    Intelligent Automation & Soft Computing, Vol.30, No.3, pp. 961-972, 2021, DOI:10.32604/iasc.2021.018242

    Abstract Real-world applications are now dealing with a huge amount of data, especially in the area of high-dimensional features. Trait reduction is one of the major steps in decision making problems. It refers to the determination of a minimum subset of attributes which preserves the final decision based on the entire set of attributes. Unfortunately, most of the current features are irrelevant or redundant, which makes these systems unreliable and imprecise. This paper proposes a new paradigm based on fuzzy soft relationship and level fuzzy soft relationship, called Union - Intersection decision making method. Using these More >

  • Open Access

    ARTICLE

    An Approach Using Fuzzy Sets and Boosting Techniques to Predict Liver Disease

    Pushpendra Kumar1,2,*, Ramjeevan Singh Thakur3

    CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3513-3529, 2021, DOI:10.32604/cmc.2021.016957

    Abstract The aim of this research is to develop a mechanism to help medical practitioners predict and diagnose liver disease. Several systems have been proposed to help medical experts by diminishing error and increasing accuracy in diagnosing and predicting diseases. Among many existing methods, a few have considered the class imbalance issues of liver disorder datasets. As all the samples of liver disorder datasets are not useful, they do not contribute to learning about classifiers. A few samples might be redundant, which can increase the computational cost and affect the performance of the classifier. In this… More >

  • Open Access

    ARTICLE

    Multi-Criteria Decision Making Based on Bipolar Picture Fuzzy Operators and New Distance Measures

    Muhammad Riaz1, Harish Garg2, Hafiz Muhammad Athar Farid1, Ronnason Chinram3,4,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.127, No.2, pp. 771-800, 2021, DOI:10.32604/cmes.2021.014174

    Abstract This paper aims to introduce the novel concept of the bipolar picture fuzzy set (BPFS) as a hybrid structure of bipolar fuzzy set (BFS) and picture fuzzy set (PFS). BPFS is a new kind of fuzzy sets to deal with bipolarity (both positive and negative aspects) to each membership degree (belonging-ness), neutral membership (not decided), and non-membership degree (refusal). In this article, some basic properties of bipolar picture fuzzy sets (BPFSs) and their fundamental operations are introduced. The score function, accuracy function and certainty function are suggested to discuss the comparability of bipolar picture fuzzy More >

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