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  • Open Access

    REVIEW

    Artificial Neural Networks and Taguchi Methods for Energy Systems Optimization: A Comprehensive Review

    Mir Majid Etghani1, Homayoun Boodaghi2,*

    Energy Engineering, Vol.122, No.11, pp. 4385-4474, 2025, DOI:10.32604/ee.2025.070668 - 27 October 2025

    Abstract Energy system optimization has become crucial for enhancing efficiency and environmental sustainability. This comprehensive review examines the synergistic application of Artificial Neural Networks (ANN) and Taguchi methods in optimizing diverse energy systems. While previous reviews have focused on these methods separately, this paper presents the first integrated analysis of both approaches across multiple energy applications. We systematically analyze their implementation in: Internal combustion engines, Thermal energy storage systems, Solar energy systems, Wind and tidal turbines, Heat exchangers, and hybrid energy systems. Our findings reveal that ANN models consistently achieve prediction accuracies exceeding 90% when compared More > Graphic Abstract

    Artificial Neural Networks and Taguchi Methods for Energy Systems Optimization: A Comprehensive Review

  • Open Access

    ARTICLE

    An Improved Interval-Valued Picture Fuzzy TOPSIS Approach Based on New Divergence Measures for Risk Assessment

    Sijia Zhu1, Yuhan Li2, Prasanalakshmi Balaji3,*, Akila Thiyagarajan3, Rajanikanth Aluvalu4, Zhe Liu5,6,7,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.2, pp. 2099-2121, 2025, DOI:10.32604/cmes.2025.068734 - 31 August 2025

    Abstract While interval-valued picture fuzzy sets (IvPFSs) provide a powerful tool for modeling uncertainty and ambiguity in various fields, existing divergence measures for IvPFSs remain limited and often produce counterintuitive results. To address these shortcomings, this paper introduces two novel divergence measures for IvPFSs, inspired by the Jensen-Shannon divergence. The fundamental properties of the proposed measures—non-degeneracy, symmetry, triangular inequality, and boundedness—are rigorously proven. Comparative analyses with existing measures are conducted through specific cases and numerical examples, clearly demonstrating the advantages of our approach. Furthermore, we apply the new divergence measures to develop an enhanced interval-valued picture More >

  • Open Access

    ARTICLE

    Adaptive Relay-Assisted WBAN Protocol: Enhancing Energy Efficiency and QoS through Advanced Multi-Criteria Decision-Making

    Surender Singh1,2,*, Naveen Bilandi1,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.1, pp. 489-509, 2025, DOI:10.32604/cmes.2025.065101 - 31 July 2025

    Abstract Wireless Body Area Network (WBAN) is essential for continuous health monitoring. However, they face energy efficiency challenges due to the low power consumption of sensor nodes. Current WBAN routing protocols face limitations in strategically minimizing energy consumption during the retrieval of vital health parameters. Efficient network traffic management remains a challenge, with existing approaches often resulting in increased delay and reduced throughput. Additionally, insufficient attention has been paid to enhancing channel capacity to maintain signal strength and mitigate fading effects under dynamic and robust operating scenarios. Several routing strategies and procedures have been developed to… More >

  • Open Access

    ARTICLE

    Application of Various Optimisation Methods in the Multi-Optimisation for Tribological Properties of Al–B4C Composites

    Sandra Gajević1, Slavica Miladinović1, Jelena Jovanović1, Onur Güler2, Serdar Özkaya2, Blaža Stojanović1,*

    CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 4341-4361, 2025, DOI:10.32604/cmc.2025.065645 - 30 July 2025

    Abstract This paper presents an investigation of the tribological performance of AA2024–B4C composites, with a specific focus on the influence of reinforcement and processing parameters. In this study three input parameters were varied: B4C weight percentage, milling time, and normal load, to evaluate their effects on two output parameters: wear loss and the coefficient of friction. AA2024 alloy was used as the matrix alloy, while B4C particles were used as reinforcement. Due to the high hardness and wear resistance of B4C, the optimized composite shows strong potential for use in aerospace structural elements and automotive brake components. The… More >

  • Open Access

    ARTICLE

    Quantum-Driven Spherical Fuzzy Model for Best Gate Security Systems

    Muhammad Amad Sarwar1,*, Yuezheng Gong1, Sarah A. Alzakari2, Amel Ali Alhussan2

    CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.3, pp. 3523-3555, 2025, DOI:10.32604/cmes.2025.066356 - 30 June 2025

    Abstract Global security threats have motivated organizations to adopt robust and reliable security systems to ensure the safety of individuals and assets. Biometric authentication systems offer a strong solution. However, choosing the best security system requires a structured decision-making framework, especially in complex scenarios involving multiple criteria. To address this problem, we develop a novel quantum spherical fuzzy technique for order preference by similarity to ideal solution (QSF-TOPSIS) methodology, integrating quantum mechanics principles and fuzzy theory. The proposed approach enhances decision-making accuracy, handles uncertainty, and incorporates criteria relationships. Criteria weights are determined using spherical fuzzy sets,… More >

  • Open Access

    ARTICLE

    A Generative Model-Based Network Framework for Ecological Data Reconstruction

    Shuqiao Liu1, Zhao Zhang2,*, Hongyan Zhou1, Xuebo Chen1

    CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 929-948, 2025, DOI:10.32604/cmc.2024.057319 - 03 January 2025

    Abstract This study examines the effectiveness of artificial intelligence techniques in generating high-quality environmental data for species introductory site selection systems. Combining Strengths, Weaknesses, Opportunities, Threats (SWOT) analysis data with Variation Autoencoder (VAE) and Generative Adversarial Network (GAN) the network framework model (SAE-GAN), is proposed for environmental data reconstruction. The model combines two popular generative models, GAN and VAE, to generate features conditional on categorical data embedding after SWOT Analysis. The model is capable of generating features that resemble real feature distributions and adding sample factors to more accurately track individual sample data. Reconstructed data is… 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

    Comprehensive Evaluation of Distributed PV Grid-Connected Based on Combined Weighting Weights and TOPSIS-RSR Method

    Yue Yang1, Jiarui Zheng1, Long Cheng1,*, Yongnan Zhu2, Hao Wu2

    Energy Engineering, Vol.121, No.3, pp. 703-728, 2024, DOI:10.32604/ee.2023.044721 - 27 February 2024

    Abstract To effectively quantify the impact of distributed photovoltaic (PV) access on the distribution network, this paper proposes a comprehensive evaluation method of distributed PV grid connection combining subjective and objective combination of assignment and technique for order preference by similarity to an ideal solution (TOPSIS)—rank sum ratio (RSR) (TOPSIS-RSR) method. Based on the traditional distribution network evaluation system, a comprehensive evaluation system has been constructed. It fully considers the new development requirements of distributed PV access on the environmental friendliness and absorptive capacity of the distribution grid and comprehensively reflects the impact of distributed PV… 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 - 29 April 2023

    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… More >

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