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  • Open Access

    ARTICLE

    Distributed Robust Scheduling Optimization of Wind-Thermal-Storage System Based on Hybrid Carbon Trading and Wasserstein Fuzzy Set

    Gang Wang*, Yuedong Wu, Xiaoyi Qian, Yi Zhao

    Energy Engineering, Vol.121, No.11, pp. 3417-3435, 2024, DOI:10.32604/ee.2024.052268 - 21 October 2024

    Abstract A robust scheduling optimization method for wind–fire storage system distribution based on the mixed carbon trading mechanism is proposed to improve the rationality of carbon emission quota allocation while reducing the instability of large-scale wind power access systems. A hybrid carbon trading mechanism that combines short-term and long-term carbon trading is constructed, and a fuzzy set based on Wasserstein measurement is proposed to address the uncertainty of wind power access. Moreover, a robust scheduling optimization method for wind–fire storage systems is formed. Results of the multi scenario comparative analysis of practical cases show that the More >

  • Open Access

    ARTICLE

    Fuzzy Multi-Criteria Decision Support System for the Best Anti-Aging Treatment Selection Process through Normal Wiggly Hesitant Fuzzy Sets

    Daekook Kang1, Ramya Lakshmanaraj2, Samayan Narayanamoorthy2, Navaneethakrishnan Suganthi Keerthana Devi2, Samayan Kalaiselvan3, Ranganathan Saraswathy4, Dragan Pamucar5,6,7,*, Vladimir Simic8,9

    CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4947-4972, 2024, DOI:10.32604/cmc.2024.055260 - 12 September 2024

    Abstract This socialized environment among educated and developed people causes them to focus more on their appearance and health, which turns them towards medical-related treatments, leading us to discuss anti-aging treatment methods for each age group, particularly for urban people who are interested in this. Some anti-aging therapies are used to address the alterations brought on by aging in human life without the need for surgery or negative effects. Five anti-aging therapies such as microdermabrasion or dermabrasion, laser resurfacing anti-aging skin treatments, chemical peels, dermal fillers for aged skin, and botox injections are considered in this… More >

  • Open Access

    ARTICLE

    A Complex Fuzzy LSTM Network for Temporal-Related Forecasting Problems

    Nguyen Tho Thong1, Nguyen Van Quyet1,2, Cu Nguyen Giap3,*, Nguyen Long Giang1, Luong Thi Hong Lan4

    CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4173-4196, 2024, DOI:10.32604/cmc.2024.054031 - 12 September 2024

    Abstract Time-stamped data is fast and constantly growing and it contains significant information thanks to the quick development of management platforms and systems based on the Internet and cutting-edge information communication technologies. Mining the time series data including time series prediction has many practical applications. Many new techniques were developed for use with various types of time series data in the prediction problem. Among those, this work suggests a unique strategy to enhance predicting quality on time-series datasets that the time-cycle matters by fusing deep learning methods with fuzzy theory. In order to increase forecasting accuracy… More >

  • Open Access

    ARTICLE

    Evaluation of Industrial IoT Service Providers with TOPSIS Based on Circular Intuitionistic Fuzzy Sets

    Elif Çaloğlu Büyükselçuk*

    CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 715-746, 2024, DOI:10.32604/cmc.2024.052509 - 18 July 2024

    Abstract Industrial Internet of Things (IIoT) service providers have become increasingly important in the manufacturing industry due to their ability to gather and process vast amounts of data from connected devices, enabling manufacturers to improve operational efficiency, reduce costs, and enhance product quality. These platforms provide manufacturers with real-time visibility into their production processes and supply chains, allowing them to optimize operations and make informed decisions. In addition, IIoT service providers can help manufacturers create new revenue streams through the development of innovative products and services and enable them to leverage the benefits of emerging technologies… More >

  • Open Access

    ARTICLE

    Fuzzy Risk Assessment Method for Airborne Network Security Based on AHP-TOPSIS

    Kenian Wang1,2,*, Yuan Hong1,2, Chunxiao Li2

    CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 1123-1142, 2024, DOI:10.32604/cmc.2024.052088 - 18 July 2024

    Abstract With the exponential increase in information security risks, ensuring the safety of aircraft heavily relies on the accurate performance of risk assessment. However, experts possess a limited understanding of fundamental security elements, such as assets, threats, and vulnerabilities, due to the confidentiality of airborne networks, resulting in cognitive uncertainty. Therefore, the Pythagorean fuzzy Analytic Hierarchy Process (AHP) Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) is proposed to address the expert cognitive uncertainty during information security risk assessment for airborne networks. First, Pythagorean fuzzy AHP is employed to construct an index system… More >

  • Open Access

    ARTICLE

    Fully Completed Spherical Fuzzy Approach-Based Z Numbers (PHI Model) for Enhanced Group Expert Consensus

    Phi-Hung Nguyen*

    CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 1655-1675, 2024, DOI:10.32604/cmc.2024.050713 - 18 July 2024

    Abstract This study aims to establish an expert consensus and enhance the efficacy of decision-making processes by integrating Spherical Fuzzy Sets (SFSs) and Z-Numbers (SFZs). A novel group expert consensus technique, the PHI model, is developed to address the inherent limitations of both SFSs and the traditional Delphi technique, particularly in uncertain, complex scenarios. In such contexts, the accuracy of expert knowledge and the confidence in their judgments are pivotal considerations. This study provides the fundamental operational principles and aggregation operators associated with SFSs and Z-numbers, encompassing weighted geometric and arithmetic operators alongside fully developed operators… More >

  • Open Access

    ARTICLE

    An Integrated Bipolar Picture Fuzzy Decision Driven System to Scrutinize Food Waste Treatment Technology through Assorted Factor Analysis

    Navaneethakrishnan Suganthi Keerthana Devi1, Samayan Narayanamoorthy1, Thirumalai Nallasivan Parthasarathy1, Chakkarapani Sumathi Thilagasree2, Dragan Pamucar3,4,*, Vladimir Simic5,6, Hasan Dinçer7,8, Serhat Yüksel7,8

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 2665-2687, 2024, DOI:10.32604/cmes.2024.050954 - 08 July 2024

    Abstract Food Waste (FW) is a pressing environmental concern that affects every country globally. About one-third of the food that is produced ends up as waste, contributing to the carbon footprint. Hence, the FW must be properly treated to reduce environmental pollution. This study evaluates a few available Food Waste Treatment (FWT) technologies, such as anaerobic digestion, composting, landfill, and incineration, which are widely used. A Bipolar Picture Fuzzy Set (BPFS) is proposed to deal with the ambiguity and uncertainty that arise when converting a real-world problem to a mathematical model. A novel Criteria Importance Through… More >

  • Open Access

    ARTICLE

    A Hybrid Machine Learning Framework for Security Intrusion Detection

    Fatimah Mudhhi Alanazi*, Bothina Abdelmeneem Elsobky, Shaimaa Aly Elmorsy

    Computer Systems Science and Engineering, Vol.48, No.3, pp. 835-851, 2024, DOI:10.32604/csse.2024.042401 - 20 May 2024

    Abstract Proliferation of technology, coupled with networking growth, has catapulted cybersecurity to the forefront of modern security concerns. In this landscape, the precise detection of cyberattacks and anomalies within networks is crucial, necessitating the development of efficient intrusion detection systems (IDS). This article introduces a framework utilizing the fusion of fuzzy sets with support vector machines (SVM), named FSVM. The core strategy of FSVM lies in calculating the significance of network features to determine their relative importance. Features with minimal significance are prudently disregarded, a method akin to feature selection. This process not only curtails the… More >

  • Open Access

    ARTICLE

    Complex Decision Modeling Framework with Fairly Operators and Quaternion Numbers under Intuitionistic Fuzzy Rough Context

    Nadeem Salamat1, Muhammad Kamran1,2,*, Shahzaib Ashraf1, Manal Elzain Mohammed Abdulla3, Rashad Ismail3, Mohammed M. Al-Shamiri3

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1893-1933, 2024, DOI:10.32604/cmes.2023.044697 - 29 January 2024

    Abstract The main goal of informal computing is to overcome the limitations of hypersensitivity to defects and uncertainty while maintaining a balance between high accuracy, accessibility, and cost-effectiveness. This paper investigates the potential applications of intuitionistic fuzzy sets (IFS) with rough sets in the context of sparse data. When it comes to capture uncertain information emanating from both upper and lower approximations, these intuitionistic fuzzy rough numbers (IFRNs) are superior to intuitionistic fuzzy sets and pythagorean fuzzy sets, respectively. We use rough sets in conjunction with IFSs to develop several fairly aggregation operators and analyze their… More > Graphic Abstract

    Complex Decision Modeling Framework with Fairly Operators and Quaternion Numbers under Intuitionistic Fuzzy Rough Context

  • Open Access

    ARTICLE

    Fuzzy Difference Equations in Diagnoses of Glaucoma from Retinal Images Using Deep Learning

    D. Dorathy Prema Kavitha1, L. Francis Raj1, Sandeep Kautish2,#, Abdulaziz S. Almazyad3, Karam M. Sallam4, Ali Wagdy Mohamed5,6,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.1, pp. 801-816, 2024, DOI:10.32604/cmes.2023.030902 - 30 December 2023

    Abstract The intuitive fuzzy set has found important application in decision-making and machine learning. To enrich and utilize the intuitive fuzzy set, this study designed and developed a deep neural network-based glaucoma eye detection using fuzzy difference equations in the domain where the retinal images converge. Retinal image detections are categorized as normal eye recognition, suspected glaucomatous eye recognition, and glaucomatous eye recognition. Fuzzy degrees associated with weighted values are calculated to determine the level of concentration between the fuzzy partition and the retinal images. The proposed model was used to diagnose glaucoma using retinal images… More >

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