Ying Su¹, Morgan C. Wang¹, Shuai Liu^2,*

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3529-3549, 2024, DOI:10.32604/cmc.2024.047189

Abstract Long-term time series forecasting stands as a crucial research domain within the realm of automated machine learning (AutoML). At present, forecasting, whether rooted in machine learning or statistical learning, typically relies on expert input and necessitates substantial manual involvement. This manual effort spans model development, feature engineering, hyper-parameter tuning, and the intricate construction of time series models. The complexity of these tasks renders complete automation unfeasible, as they inherently demand human intervention at multiple junctures. To surmount these challenges, this article proposes leveraging Long Short-Term Memory, which is the variant of Recurrent Neural Networks, harnessing memory cells and gating mechanisms… More >

Navaneetha Krishnan Muthunambu¹, Senthil Prabakaran², Balasubramanian Prabhu Kavin³, Kishore Senthil Siruvangur⁴, Kavitha Chinnadurai¹, Jehad Ali^5,*

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3089-3127, 2024, DOI:10.32604/cmc.2023.043172

Abstract The extensive utilization of the Internet in everyday life can be attributed to the substantial accessibility of online services and the growing significance of the data transmitted via the Internet. Regrettably, this development has expanded the potential targets that hackers might exploit. Without adequate safeguards, data transmitted on the internet is significantly more susceptible to unauthorized access, theft, or alteration. The identification of unauthorised access attempts is a critical component of cybersecurity as it aids in the detection and prevention of malicious attacks. This research paper introduces a novel intrusion detection framework that utilizes Recurrent Neural Networks (RNN) integrated with… More >

Yajing Ma^1,2,3, Gulila Altenbek^1,2,3,*, Yingxia Yu¹

CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 695-712, 2024, DOI:10.32604/cmc.2023.045486

Abstract Due to the structural dependencies among concurrent events in the knowledge graph and the substantial amount of sequential correlation information carried by temporally adjacent events, we propose an Independent Recurrent Temporal Graph Convolution Networks (IndRT-GCNets) framework to efficiently and accurately capture event attribute information. The framework models the knowledge graph sequences to learn the evolutionary representations of entities and relations within each period. Firstly, by utilizing the temporal graph convolution module in the evolutionary representation unit, the framework captures the structural dependency relationships within the knowledge graph in each period. Meanwhile, to achieve better event representation and establish effective correlations,… More >

Wei Wang¹, Yang Yu¹, Simin Luo^2,*, Wenlin Liu², Wei Tang¹, Yuanbo Ye¹

Energy Engineering, Vol.121, No.2, pp. 315-337, 2024, DOI:10.32604/ee.2023.042082

Abstract As an effective approach to achieve the “dual-carbon” goal, the grid-connected capacity of renewable energy increases constantly. Photovoltaics are the most widely used renewable energy sources and have been applied on various occasions. However, the inherent randomness, intermittency, and weak support of grid-connected equipment not only cause changes in the original flow characteristics of the grid but also result in complex fault characteristics. Traditional overcurrent and differential protection methods cannot respond accurately due to the effects of unknown renewable energy sources. Therefore, a longitudinal protection method based on virtual measurement of current restraint is proposed in this paper. The positive… More >

Hasna Akarni^*, Hamza Mabchour, Laila El Aarabi, Soumia Mordane

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.3, pp. 579-593, 2024, DOI:10.32604/fdmp.2023.043080

Abstract In this study, we focus on the numerical modelling of the interaction between waves and submerged structures in the presence of a uniform flow current. Both the same and opposite senses of wave propagation are considered. The main objective is an understanding of the effect of the current and various geometrical parameters on the reflection coefficient. The wave used in the study is based on potential theory, and the submerged structures consist of two rectangular breakwaters positioned at a fixed distance from each other and attached to the bottom of a wave flume. The numerical modeling approach employed in this… More >

Longteng Liang^1,2,3, Zhouquan Feng^2,4,*, Hongyi Zhang^2,4, Zhengqing Chen^2,4, Changzhao Qian^1,3

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2403-2419, 2024, DOI:10.32604/cmes.2023.031260

Abstract Eddy current dampers (ECDs) have emerged as highly desirable solutions for vibration control due to their exceptional damping performance and durability. However, the existing constitutive models present challenges to the widespread implementation of ECD technology, and there is limited availability of finite element analysis (FEA) software capable of accurately modeling the behavior of ECDs. This study addresses these issues by developing a new constitutive model that is both easily understandable and user-friendly for FEA software. By utilizing numerical results obtained from electromagnetic FEA, a novel power law constitutive model is proposed to capture the nonlinear behavior of ECDs. The effectiveness… More >

Tomoki Hirokawa^a,*, Masahiko Murozono^a, Oleg Kabov^b,c, Haruhiko Ohta^a

Frontiers in Heat and Mass Transfer, Vol.5, pp. 1-8, 2014, DOI:10.5098/hmt.5.17

Abstract Experiments are performed to study the liquid film behavior and corresponding local heat transfer to shear-driven liquid film flow of water in the cocurrent nitrogen gas flow. The heated channel has a cross section of 30mm in width and 5mm in height, where the bottom is operated as a heating surface of 30mm in width and 100mm in length. The heated section is divided into segments to evaluate the local heat transfer coefficients. Under most gas Reynolds numbers, the local heat transfer coefficients are increased with increasing heat flux, where three mechanisms are important; (i) increase of areas along the… More >

Dazhi Wang^*, Pengyi Pan, Bowen Niu

CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 1535-1555, 2023, DOI:10.32604/cmc.2023.042286

Abstract The permanent magnet eddy current coupler (PMEC) solves the problem of flexible connection and speed regulation between the motor and the load and is widely used in electrical transmission systems. It provides torque to the load and generates heat and losses, reducing its energy transfer efficiency. This issue has become an obstacle for PMEC to develop toward a higher power. This paper aims to improve the overall performance of PMEC through multi-objective optimization methods. Firstly, a PMEC modeling method based on the Levenberg-Marquardt back propagation (LMBP) neural network is proposed, aiming at the characteristics of the complex input-output relationship and… More >

Muhammad Usman Ghani Khan¹, Abid Mehmood², Mourad Elhadef², Shehzad Ashraf Chaudhry^2,3,*

CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 2225-2249, 2023, DOI:10.32604/cmc.2023.038303

Abstract The proliferation of deluding data such as fake news and phony audits on news web journals, online publications, and internet business apps has been aided by the availability of the web, cell phones, and social media. Individuals can quickly fabricate comments and news on social media. The most difficult challenge is determining which news is real or fake. Accordingly, tracking down programmed techniques to recognize fake news online is imperative. With an emphasis on false news, this study presents the evolution of artificial intelligence techniques for detecting spurious social media content. This study shows past, current, and possible methods that… More >

J. K. Singh^a,*, N. Joshi^a , S. G. Begum^a, C. T. Srinivasa^b

Frontiers in Heat and Mass Transfer, Vol.7, pp. 1-12, 2016, DOI:10.5098/hmt.7.24

Abstract In the present analytical study, we have considered unsteady hydromagnetic heat and mass transfer natural convection flow of an electrically conducting, heat absorbing and chemically reacting fluid past an exponentially accelerated vertical plate in a uniform porous medium taking Hall current and rotation into account. The species concentration near the plate is considered to be varies linearly with time. Two particular cases for plate temperature are considered i.e. (i) plate temperature is uniform and (ii) plate temperature varies linearly with time and after some time it is maintained at uniform temperature. The coupled partial differential equations governing the fluid flow… More >