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  • Open Access


    Prediction and Analysis of Vehicle Interior Road Noise Based on Mechanism and Data Series Modeling

    Jian Pang1,3, Tingting Mao2, Wenyu Jia3, Xiaoli Jia3,*, Peisong Dai2, Haibo Huang1,2,*

    Sound & Vibration, Vol.58, pp. 59-80, 2024, DOI:10.32604/sv.2024.046247

    Abstract Currently, the inexorable trend toward the electrification of automobiles has heightened the prominence of road noise within overall vehicle noise. Consequently, an in-depth investigation into automobile road noise holds substantial practical importance. Previous research endeavors have predominantly centered on the formulation of mechanism models and data-driven models. While mechanism models offer robust controllability, their application encounters challenges in intricate analyses of vehicle body acoustic-vibration coupling, and the effective utilization of accumulated data remains elusive. In contrast, data-driven models exhibit efficient modeling capabilities and can assimilate conceptual vehicle knowledge, but they impose stringent requirements on both data quality and quantity. In… More >

  • Open Access


    News Modeling and Retrieving Information: Data-Driven Approach

    Elias Hossain1, Abdullah Alshahrani2, Wahidur Rahman3,*

    Intelligent Automation & Soft Computing, Vol.38, No.2, pp. 109-123, 2023, DOI:10.32604/iasc.2022.029511

    Abstract This paper aims to develop Machine Learning algorithms to classify electronic articles related to this phenomenon by retrieving information and topic modelling. The Methodology of this study is categorized into three phases: the Text Classification Approach (TCA), the Proposed Algorithms Interpretation (PAI), and finally, Information Retrieval Approach (IRA). The TCA reflects the text preprocessing pipeline called a clean corpus. The Global Vectors for Word Representation (Glove) pre-trained model, FastText, Term Frequency-Inverse Document Frequency (TF-IDF), and Bag-of-Words (BOW) for extracting the features have been interpreted in this research. The PAI manifests the Bidirectional Long Short-Term Memory (Bi-LSTM) and Convolutional Neural Network… More >

  • Open Access


    Emerging Trends in Damage Tolerance Assessment: A Review of Smart Materials and Self-Repairable Structures

    Ali Akbar Firoozi1,*, Ali Asghar Firoozi2

    Structural Durability & Health Monitoring, Vol.18, No.1, pp. 1-18, 2024, DOI:10.32604/sdhm.2023.044573

    Abstract The discipline of damage tolerance assessment has experienced significant advancements due to the emergence of smart materials and self-repairable structures. This review offers a comprehensive look into both traditional and innovative methodologies employed in damage tolerance assessment. After a detailed exploration of damage tolerance concepts and their historical progression, the review juxtaposes the proven techniques of damage assessment with the cutting-edge innovations brought about by smart materials and self-repairable structures. The subsequent sections delve into the synergistic integration of smart materials with self-repairable structures, marking a pivotal stride in damage tolerance by establishing an autonomous system for immediate damage identification… More >

  • Open Access


    Expert Experience and Data-Driven Based Hybrid Fault Diagnosis for High-Speed Wire Rod Finishing Mills

    Cunsong Wang1, Ningze Tang1, Quanling Zhang1,*, Lixin Gao2, Haichen Yin3, Hao Peng4

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1827-1847, 2024, DOI:10.32604/cmes.2023.030970

    Abstract The reliable operation of high-speed wire rod finishing mills is crucial in the steel production enterprise. As complex system-level equipment, it is difficult for high-speed wire rod finishing mills to realize fault location and real-time monitoring. To solve the above problems, an expert experience and data-driven-based hybrid fault diagnosis method for high-speed wire rod finishing mills is proposed in this paper. First, based on its mechanical structure, time and frequency domain analysis are improved in fault feature extraction. The approach of combining virtual value, peak value with kurtosis value index, is adopted in time domain analysis. Speed adjustment and side… More >

  • Open Access


    Multi-Objective Prediction and Optimization of Vehicle Acoustic Package Based on ResNet Neural Network

    Yunru Wu1, Xiangbo Liu1, Haibo Huang1,2,*, Yudong Wu1, Weiping Ding1,2, Mingliang Yang1,2,*

    Sound & Vibration, Vol.57, pp. 73-95, 2023, DOI:10.32604/sv.2023.044601

    Abstract Vehicle interior noise has emerged as a crucial assessment criterion for automotive NVH (Noise, Vibration, and Harshness). When analyzing the NVH performance of the vehicle body, the traditional SEA (Statistical Energy Analysis) simulation technology is usually limited by the accuracy of the material parameters obtained during the acoustic package modeling and the limitations of the application conditions. In order to effectively solve these shortcomings, based on the analysis of the vehicle noise transmission path, a multi-level objective decomposition architecture of the interior noise at the driver’s right ear is established. Combined with the data-driven method, the ResNet neural network model… More >

  • Open Access


    Parallel Integrated Model-Driven and Data-Driven Online Transient Stability Assessment Method for Power System

    Ying Zhang1, Xiaoqing Han2, Chao Zhang1, Ying Qu1, Yang Liu1, Gengwu Zhang2,*

    Energy Engineering, Vol.120, No.11, pp. 2585-2609, 2023, DOI:10.32604/ee.2023.026816

    Abstract More and more uncertain factors in power systems and more and more complex operation modes of power systems put forward higher requirements for online transient stability assessment methods. The traditional model-driven methods have clear physical mechanisms and reliable evaluation results but the calculation process is time-consuming, while the data-driven methods have the strong fitting ability and fast calculation speed but the evaluation results lack interpretation. Therefore, it is a future development trend of transient stability assessment methods to combine these two kinds of methods. In this paper, the rate of change of the kinetic energy method is used to calculate… More >

  • Open Access


    Improved Transportation Model with Internet of Things Using Artificial Intelligence Algorithm

    Ayman Khallel Al-Ani1,*, Shams Ul Arfeen Laghari2, Hariprasath Manoharan3, Shitharth Selvarajan4, Mueen Uddin5

    CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 2261-2279, 2023, DOI:10.32604/cmc.2023.038534

    Abstract In this paper, the application of transportation systems in real-time traffic conditions is evaluated with data handling representations. The proposed method is designed in such a way as to detect the number of loads that are present in a vehicle where functionality tasks are computed in the system. Compared to the existing approach, the design model in the proposed method is made by dividing the computing areas into several cluster regions, thereby reducing the complex monitoring system where control errors are minimized. Furthermore, a route management technique is combined with Artificial Intelligence (AI) algorithm to transmit the data to appropriate… More >

  • Open Access


    A Data-Driven Model for Real-Time Simulation of the Contact Detumbling of Satellites

    Hao Chen1, Honghua Dai1, Xiaokui Yue1

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.26, No.1, pp. 1-1, 2023, DOI:10.32604/icces.2023.09145

    Abstract The number of malfunctioning satellites is dramatically increasing with the development of space technology in recent decades. These malfunctioning satellites are normally in rotating or tumbling states due to residual angular momentum, gravity gradient, et al, making direct capture impossible. Therefore, stabilizing these objects within acceptable angular velocities is an indispensable stage for in-orbit capture. The contact method using a flexible device (e.g., brush or rod) to detumble these satellites is considered to be safe and efficient enough. However, it is extremely time-consuming to solve the dynamic model of the detumbling system, which is a very tricky problem for in-orbit… More >

  • Open Access


    Data-Driven Enhanced Combined Finite-Discrete Element Method for Simulating Rock Failure Progress

    Ruifeng Zhao1, Zhijun Wu1,*

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.25, No.1, pp. 1-2, 2023, DOI:10.32604/icces.2023.09814

    Abstract The combined finite-discrete element method (FDEM) can effectively simulate the continuousdiscontinuous failure process of rocks, and is now widely adopted to investigate the issues related to rock mechanics and engineering. The conventional FDEM requires pre-defines constitutive models to calculate the element stress from element deformations [1]. However, the constitutive model used in conventional FDEM is obtained by empirical fitting of rock mechanics test data, and large amount of rock physical and mechanical information present in the test data, such as the nonlinear properties of rock presented in the initial compaction stage, are lost in the process of fitting test data… More >

  • Open Access


    Intelligent Intrusion Detection System for the Internet of Medical Things Based on Data-Driven Techniques

    Okba Taouali1,*, Sawcen Bacha2, Khaoula Ben Abdellafou1, Ahamed Aljuhani1, Kamel Zidi3, Rehab Alanazi1, Mohamed Faouzi Harkat4

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 1593-1609, 2023, DOI:10.32604/csse.2023.039984

    Abstract Introducing IoT devices to healthcare fields has made it possible to remotely monitor patients’ information and provide a proper diagnosis as needed, resulting in the Internet of Medical Things (IoMT). However, obtaining good security features that ensure the integrity and confidentiality of patient’s information is a significant challenge. However, due to the computational resources being limited, an edge device may struggle to handle heavy detection tasks such as complex machine learning algorithms. Therefore, designing and developing a lightweight detection mechanism is crucial. To address the aforementioned challenges, a new lightweight IDS approach is developed to effectively combat a diverse range… More >

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