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  • Open Access

    ARTICLE

    Information Security Evaluation of Industrial Control Systems Using Probabilistic Linguistic MCDM Method

    Wenshu Xu, Mingwei Lin*

    CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 199-222, 2023, DOI:10.32604/cmc.2023.041475

    Abstract Industrial control systems (ICSs) are widely used in various fields, and the information security problems of ICSs are increasingly serious. The existing evaluation methods fail to describe the uncertain evaluation information and group evaluation information of experts. Thus, this paper introduces the probabilistic linguistic term sets (PLTSs) to model the evaluation information of experts. Meanwhile, we propose a probabilistic linguistic multi-criteria decision-making (PL-MCDM) method to solve the information security assessment problem of ICSs. Firstly, we propose a novel subscript equivalence distance measure of PLTSs to improve the existing methods. Secondly, we use the Best Worst Method (BWM) method and Criteria… More >

  • Open Access

    ARTICLE

    Threat Modeling and Application Research Based on Multi-Source Attack and Defense Knowledge

    Shuqin Zhang, Xinyu Su*, Peiyu Shi, Tianhui Du, Yunfei Han

    CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 349-377, 2023, DOI:10.32604/cmc.2023.040964

    Abstract Cyber Threat Intelligence (CTI) is a valuable resource for cybersecurity defense, but it also poses challenges due to its multi-source and heterogeneous nature. Security personnel may be unable to use CTI effectively to understand the condition and trend of a cyberattack and respond promptly. To address these challenges, we propose a novel approach that consists of three steps. First, we construct the attack and defense analysis of the cybersecurity ontology (ADACO) model by integrating multiple cybersecurity databases. Second, we develop the threat evolution prediction algorithm (TEPA), which can automatically detect threats at device nodes, correlate and map multi-source threat information,… More >

  • Open Access

    ARTICLE

    An Intelligent Algorithm for Solving Weapon-Target Assignment Problem: DDPG-DNPE Algorithm

    Tengda Li, Gang Wang, Qiang Fu*, Xiangke Guo, Minrui Zhao, Xiangyu Liu

    CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3499-3522, 2023, DOI:10.32604/cmc.2023.041253

    Abstract Aiming at the problems of traditional dynamic weapon-target assignment algorithms in command decision-making, such as large computational amount, slow solution speed, and low calculation accuracy, combined with deep reinforcement learning theory, an improved Deep Deterministic Policy Gradient algorithm with dual noise and prioritized experience replay is proposed, which uses a double noise mechanism to expand the search range of the action, and introduces a priority experience playback mechanism to effectively achieve data utilization. Finally, the algorithm is simulated and validated on the ground-to-air countermeasures digital battlefield. The results of the experiment show that, under the framework of the deep neural… More >

  • Open Access

    ARTICLE

    Multi-Criteria Decision-Making for Power Grid Construction Project Investment Ranking Based on the Prospect Theory Improved by Rewarding Good and Punishing Bad Linear Transformation

    Shun Ma1, Na Yu1, Xiuna Wang2, Shiyan Mei1, Mingrui Zhao2,*, Xiaoyu Han2

    Energy Engineering, Vol.120, No.10, pp. 2369-2392, 2023, DOI:10.32604/ee.2023.028727

    Abstract Using the improved prospect theory with the linear transformations of rewarding good and punishing bad (RGPBIT), a new investment ranking model for power grid construction projects (PGCPs) is proposed. Given the uncertainty of each index value under the market environment, fuzzy numbers are used to describe qualitative indicators and interval numbers are used to describe quantitative ones. Taking into account decision-maker’s subjective risk attitudes, a multi-criteria decision-making (MCDM) method based on improved prospect theory is proposed. First, the [−1, 1] RGPBIT operator is proposed to normalize the original data, to obtain the best and worst schemes of PGCPs. Furthermore, the… More >

  • Open Access

    ARTICLE

    Machine Learning-Based Decision-Making Mechanism for Risk Assessment of Cardiovascular Disease

    Cheng Wang1, Haoran Zhu2,*, Congjun Rao2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.1, pp. 691-718, 2024, DOI:10.32604/cmes.2023.029258

    Abstract Cardiovascular disease (CVD) has gradually become one of the main causes of harm to the life and health of residents. Exploring the influencing factors and risk assessment methods of CVD has become a general trend. In this paper, a machine learning-based decision-making mechanism for risk assessment of CVD is designed. In this mechanism, the logistics regression analysis method and factor analysis model are used to select age, obesity degree, blood pressure, blood fat, blood sugar, smoking status, drinking status, and exercise status as the main pathogenic factors of CVD, and an index system of risk assessment for CVD is established.… More >

  • Open Access

    REVIEW

    Embracing the Future: AI and ML Transforming Urban Environments in Smart Cities

    Gagan Deep*, Jyoti Verma

    Journal on Artificial Intelligence, Vol.5, pp. 57-73, 2023, DOI:10.32604/jai.2023.043329

    Abstract This research explores the increasing importance of Artificial Intelligence (AI) and Machine Learning (ML) with relation to smart cities. It discusses the AI and ML’s ability to revolutionize various aspects of urban environments, including infrastructure, governance, public safety, and sustainability. The research presents the definition and characteristics of smart cities, highlighting the key components and technologies driving initiatives for smart cities. The methodology employed in this study involved a comprehensive review of relevant literature, research papers, and reports on the subject of AI and ML in smart cities. Various sources were consulted to gather information on the integration of AI… More >

  • Open Access

    ARTICLE

    Business Blockchain Suitability Determinants: Decision-Making through an Intuitionistic Fuzzy Method

    Tomader Almeshal1,*, Jawad Berri1, Tarifa Almulhim2, Areej Alhogail1, Emam Ahmed3

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 1665-1690, 2023, DOI:10.32604/csse.2023.038871

    Abstract Blockchain is one of the innovative and disruptive technologies that has a wide range of applications in multiple industries beyond cryptocurrency. The widespread adoption of blockchain technology in various industries has shown its potential to solve challenging business problems, as well as the possibility to create new business models which can increase a firm’s competitiveness. Due to the novelty of the technology, whereby many companies are still exploring potential use cases, and considering the complexity of blockchain technology, which may require huge changes to a company’s existing systems and processes, it is important for companies to carefully evaluate suitable use… More >

  • Open Access

    ARTICLE

    Multi-Attribute Group Decision-Making Method under Spherical Fuzzy Bipolar Soft Expert Framework with Its Application

    Mohammed M. Ali Al-Shamiri1,2, Ghous Ali3,*, Muhammad Zain Ul Abidin3, Arooj Adeel3

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1891-1936, 2023, DOI:10.32604/cmes.2023.027844

    Abstract Spherical fuzzy soft expert set (SFSES) theory blends the perks of spherical fuzzy sets and group decision-making into a unified approach. It allows solutions to highly complicated uncertainties and ambiguities under the unbiased supervision and group decision-making of multiple experts. However, SFSES theory has some deficiencies such as the inability to interpret and portray the bipolarity of decision-parameters. This work highlights and overcomes these limitations by introducing the novel spherical fuzzy bipolar soft expert sets (SFBSESs) as a powerful hybridization of spherical fuzzy set theory with bipolar soft expert sets (BSESs). Followed by the development of certain set-theoretic operations and… More > Graphic Abstract

    Multi-Attribute Group Decision-Making Method under Spherical Fuzzy Bipolar Soft Expert Framework with Its Application

  • Open Access

    ARTICLE

    Optimizing Decision-Making of A Smart Prosumer Microgrid Using Simulation

    Oussama Accouche1,*, Rajan Kumar Gangadhari2

    CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 151-173, 2023, DOI:10.32604/cmc.2023.038648

    Abstract Distributed renewable energy sources offer significant alternatives for Qatar and the Arab Gulf region’s future fuel supply and demand. Microgrids are essential for providing dependable power in difficult-to-reach areas while incorporating significant amounts of renewable energy sources. In energy-efficient data centers, distributed generation can be used to meet the facility’s overall power needs. This study primarily focuses on the best energy management practices for a smart microgrid in Qatar while taking demand-side load management into account. This article looked into a university microgrid in Qatar that primarily aimed to get all of its energy from the grid. While diesel generators… More >

  • Open Access

    ARTICLE

    Two-Sided Matching Decision Making with Multi-Attribute Probabilistic Hesitant Fuzzy Sets

    Peichen Zhao1, Qi Yue2,*, Zhibin Deng3

    Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 849-873, 2023, DOI:10.32604/iasc.2023.037090

    Abstract In previous research on two-sided matching (TSM) decision, agents’ preferences were often given in the form of exact values of ordinal numbers and linguistic phrase term sets. Nowdays, the matching agent cannot perform the exact evaluation in the TSM situations due to the great fuzziness of human thought and the complexity of reality. Probability hesitant fuzzy sets, however, have grown in popularity due to their advantages in communicating complex information. Therefore, this paper develops a TSM decision-making approach with multi-attribute probability hesitant fuzzy sets and unknown attribute weight information. The agent attribute weight vector should be obtained by using the… More >

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