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  • Open Access

    ARTICLE

    On Soft Pre-Rough Approximation Space with Applications in Decision Making

    M. El Sayed1,*, Wadia Faid Hassan Al-shameri1, M. A. El Safty2

    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.3, pp. 865-879, 2022, DOI:10.32604/cmes.2022.020066 - 27 June 2022

    Abstract A soft, rough set model is a distinctive mathematical model that can be used to relate a variety of real-life data. In the present work, we introduce new concepts of rough set based on soft pre-lower and soft pre-upper approximation space. These concepts are soft pre-rough equality, soft pre-rough inclusion, soft pre-rough belonging, soft predefinability, soft pre-internal lower, and soft pre-external lower. We study the properties of these concepts. Finally, we use the soft pre-rough approximation to illustrate the importance of our method in decision-making for Chikungunya medical illnesses. In reality, the impact factors of More >

  • Open Access

    ARTICLE

    Fuzzy Multi-criteria Decision Making for Decision Support in Port Capacity Upgrade

    Chia-Nan Wang, Tien–Lin Chao*

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 2485-2494, 2022, DOI:10.32604/cmc.2022.026682 - 16 June 2022

    Abstract In many port capacity upgrade projects, choosing a supplier of equipment is a complicated decision, project managers must consider many criteria to choose a supplier to ensure the project is completed on time, optimal in terms of benefit and cost. Therefore, selecting the equipment supplier in this project is a multi-criteria decision-making process. The multi-criteria decision-making (MCDM) model is applied in many fields to select the optimal solution, but there are very few studies using the MCDM model to support project managers in evaluating and selecting optimal solutions in port capacity upgrade project. In this More >

  • Open Access

    ARTICLE

    Aczel-Alsina Weighted Aggregation Operators of Simplified Neutrosophic Numbers and Its Application in Multiple Attribute Decision Making

    Rui Yong1,2,*, Jun Ye1,2, Shigui Du1,2, Aqin Zhu1, Yingying Zhang1

    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.2, pp. 569-584, 2022, DOI:10.32604/cmes.2022.019509 - 15 June 2022

    Abstract The simplified neutrosophic number (SNN) can represent uncertain, imprecise, incomplete, and inconsistent information that exists in scientific, technological, and engineering fields. Hence, it is a useful tool for describing truth, falsity, and indeterminacy information in multiple attribute decision-making (MADM) problems. To suit decision makers’ preference selection, the operational flexibility of aggregation operators shows its importance in dealing with the flexible decision-making problems in the SNN environment. To solve this problem, this paper develops the Aczel-Alsina aggregation operators of SNNs for MADM problems in view of the Aczel-Alsina operational flexibility. First, we define the Aczel-Alsina operations More >

  • Open Access

    ARTICLE

    Interval-Valued Neutrosophic Soft Expert Set from Real Space to Complex Space

    Faisal Al-Sharqi1,2, Abd Ghafur Ahmad1,*, Ashraf Al-Quran3

    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.1, pp. 267-293, 2022, DOI:10.32604/cmes.2022.019684 - 02 June 2022

    Abstract A fuzzy system is a novel computing technique that accesses uncertain information by fuzzy representation. In the decision-making process, fuzzy system and soft computing are effective tools that are tolerant to imprecision, uncertainty, and partial truths. Evolutionary fuzzy systems have been developed with the appearance of interval fuzzy, dual fuzzy, hesitant fuzzy, neutrosophic, plithogenic representations, etc. Moreover, by capturing compound features and convey multi-dimensional data, complex numbers are utilized to generalize fuzzy and neutrosophic fuzzy sets. In this paper, a representation of neutrosophic soft expert systems based on the real and complex numbers in the… More >

  • Open Access

    ARTICLE

    Privacy Preserving Image Encryption with Deep Learning Based IoT Healthcare Applications

    Mohammad Alamgeer1, Saud S. Alotaibi2, Shaha Al-Otaibi3, Nazik Alturki3, Anwer Mustafa Hilal4,*, Abdelwahed Motwakel4, Ishfaq Yaseen4, Mohamed I. Eldesouki5

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1159-1175, 2022, DOI:10.32604/cmc.2022.028275 - 18 May 2022

    Abstract Latest developments in computing and communication technologies are enabled the design of connected healthcare system which are mainly based on IoT and Edge technologies. Blockchain, data encryption, and deep learning (DL) models can be utilized to design efficient security solutions for IoT healthcare applications. In this aspect, this article introduces a Blockchain with privacy preserving image encryption and optimal deep learning (BPPIE-ODL) technique for IoT healthcare applications. The proposed BPPIE-ODL technique intends to securely transmit the encrypted medical images captured by IoT devices and performs classification process at the cloud server. The proposed BPPIE-ODL technique… More >

  • Open Access

    ARTICLE

    Fuzzy Multi-Criteria Decision Making for Solar Power Plant Location Selection

    Thai Hoang Tuyet Nhi1, Chia-Nan Wang1, Nguyen Van Thanh2,*

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4853-4865, 2022, DOI:10.32604/cmc.2022.026374 - 21 April 2022

    Abstract Vietnam is one of Southeast Asian countries with a rapid GDP growth rate, ranging from 6.5% to 7% annually, leading to an average increase in energy demand of 11% per year. This demand creates many new opportunities in the energy industry, especially renewable energy, to ensure sustainable development in the future for the country with applications of solar energy growing at the present, and other opportunities to expand in the future. In Vietnam, thanks to favorable weather, climate, terrain characteristics and many preferential support policies, there are many great opportunities in the field of solar More >

  • Open Access

    ARTICLE

    Aggregation Operators for Interval-Valued Pythagorean Fuzzy So Set with Their Application to Solve Multi-Attribute Group Decision Making Problem

    Rana Muhammad Zulqarnain1, Imran Siddique2, Aiyared Iampan3, Dumitru Baleanu4,5,6,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.3, pp. 1717-1750, 2022, DOI:10.32604/cmes.2022.019408 - 19 April 2022

    Abstract Interval-valued Pythagorean fuzzy so set (IVPFSS) is a generalization of the interval-valued intuitionistic fuzzy so set (IVIFSS) and interval-valued Pythagorean fuzzy set (IVPFS). The IVPFSS handled more uncertainty comparative to IVIFSS; it is the most signicant technique for explaining fuzzy information in the decision-making process. In this work, some novel operational laws for IVPFSS have been proposed. Based on presented operational laws, two innovative aggregation operators (AOs) have been developed such as interval-valued Pythagorean fuzzy so weighted average (IVPFSWA) and interval-valued Pythagorean fuzzy so weighted geometric (IVPFSWG) operators with their fundamental properties. A multi-attribute group More >

  • Open Access

    ARTICLE

    Power Quality Assessment Based on Rough AHP and Extension Analysis

    Guofeng Liu*, Can Zhang, Zhengyi Zhu, Xuyan Wang

    Energy Engineering, Vol.119, No.3, pp. 929-946, 2022, DOI:10.32604/ee.2022.014816 - 31 March 2022

    Abstract Due to the increasing power consumption of whole society and widely using of new non-linear and asymmetric electrical equipment, power quality assessment problem in the new period has attracted more and more attention. The mathematical essence of comprehensive assessment of power quality is a multi-attribute optimal decision-making problem. In order to solve the key problem of determining the indicator weight in the process of power quality assessment, a rough analytic hierarchy process (AHP) is proposed to aggregate the judgment opinions of multiple experts and eliminate the subjective effects of single expert judgment. Based on the… 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

    Design of Machine Learning Based Smart Irrigation System for Precision Agriculture

    Khalil Ibrahim Mohammad Abuzanouneh1, Fahd N. Al-Wesabi2, Amani Abdulrahman Albraikan3, Mesfer Al Duhayyim4, M. Al-Shabi5, Anwer Mustafa Hilal6, Manar Ahmed Hamza6,*, Abu Sarwar Zamani6, K. Muthulakshmi7

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 109-124, 2022, DOI:10.32604/cmc.2022.022648 - 24 February 2022

    Abstract Agriculture 4.0, as the future of farming technology, comprises numerous key enabling technologies towards sustainable agriculture. The use of state-of-the-art technologies, such as the Internet of Things, transform traditional cultivation practices, like irrigation, to modern solutions of precision agriculture. To achieve effective water resource usage and automated irrigation in precision agriculture, recent technologies like machine learning (ML) can be employed. With this motivation, this paper design an IoT and ML enabled smart irrigation system (IoTML-SIS) for precision agriculture. The proposed IoTML-SIS technique allows to sense the parameters of the farmland and make appropriate decisions for… More >

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