Nur Fairuz Mohamed Yusof¹, Dahaman Ishak², Muhammad Ammirrul Atiqi Mohd Zainuri^3,*, Muhammad Najwan Hamidi², Zuhair Muhammed Alaas⁴, Mohamed Mostafa Ramadan Ahmed⁵

Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 2441-2457, 2023, DOI:10.32604/iasc.2023.037778 - 21 June 2023

Abstract Grid-connected reactive-load compensation and harmonic control are becoming a central topic as photovoltaic (PV) grid-connected systems diversified. This research aims to produce a high-performance inverter with a fast dynamic response for accurate reference tracking and a low total harmonic distortion (THD) even under nonlinear load applications by improving its control scheme. The proposed system is expected to operate in both stand-alone mode and grid-connected mode. In stand-alone mode, the proposed controller supplies power to critical loads, alternatively during grid-connected mode provide excess energy to the utility. A modified variable step incremental conductance (VS-InCond) algorithm is… More >

T. Karthikeyan^1,*, M. Govindarajan¹, V. Vijayakumar²

Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 1483-1498, 2023, DOI:10.32604/iasc.2023.037606 - 21 June 2023

Abstract Frauds don’t follow any recurring patterns. They require the use of unsupervised learning since their behaviour is continually changing. Fraudsters have access to the most recent technology, which gives them the ability to defraud people through online transactions. Fraudsters make assumptions about consumers’ routine behaviour, and fraud develops swiftly. Unsupervised learning must be used by fraud detection systems to recognize online payments since some fraudsters start out using online channels before moving on to other techniques. Building a deep convolutional neural network model to identify anomalies from conventional competitive swarm optimization patterns with a focus… More >

Tiankui Sun^1,*, Mingming Shi¹, Xiaolong Xiao¹, Ping He¹, Yu Ji¹, Zhiyuan Yuan²

Energy Engineering, Vol.120, No.7, pp. 1621-1636, 2023, DOI:10.32604/ee.2023.026948 - 04 May 2023

Abstract To reduce current harmonics caused by switching frequency, T-type grid-connected inverter topology with LCL filter is adopted. In view of the disadvantages of the slow response speed of the traditional current control and the failure to eliminate the influence of the LCL filter on the grid-connected current by using current PI control alone, a current double closed loop PI current tracking control is proposed. Through the theoretical analysis of the grid-connected inverter control principle, the grid-connected inverter control model is designed, and the transfer function model of each control link is deduced, and the current More >

S. Balaji^*, S. Karthik

Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 727-743, 2023, DOI:10.32604/iasc.2023.037409 - 29 April 2023

Abstract The creation of national energy strategy cannot proceed without accurate projections of future electricity consumption; this is because EC is intimately tied to other forms of energy, such as oil and natural gas. For the purpose of determining and bettering overall energy consumption, there is an urgent requirement for accurate monitoring and calculation of EC at the building level using cutting-edge technology such as data analytics and the internet of things (IoT). Soft computing is a subset of AI that tries to design procedures that are more accurate and reliable, and it has proven to… More >

Song Yu^*, Chen Wang

CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 5555-5571, 2023, DOI:10.32604/cmc.2023.038162 - 29 April 2023

Abstract PM_2.5 has a non-negligible impact on visibility and air quality as an important component of haze and can affect cloud formation and rainfall and thus change the climate, and it is an evaluation indicator of air pollution level. Achieving PM_2.5 concentration prediction based on relevant historical data mining can effectively improve air pollution forecasting ability and guide air pollution prevention and control. The past methods neglected the impact caused by PM_2.5 flow between cities when analyzing the impact of inter-city PM_2.5 concentrations, making it difficult to further improve the prediction accuracy. However, factors including geographical information such… More >

D. Santhi Kumari^a,* , Venkata Subrahmanyam Sajja^a , P. M. Kishore^b,†

Frontiers in Heat and Mass Transfer, Vol.20, pp. 1-11, 2023, DOI:10.5098/hmt.20.5

Abstract The aim of present study is an influence of viscous dissipation and heat source on an unsteady MHD mixed convective, fluid flow past an impulsively started oscillating plate embedded in a porous medium in presence of magnetic field, heat and mass transfer. The modeling equations are converted to dimensionless equations then solved through Galerkin finite element method and discussed in the flow distributions with the help of MATLAB. Numerical results for the velocity, temperature and concentration distributions as well as the skin-friction coefficient, Nusselt number and Sherwood number are discussed in detail and displayed graphically More >

Guangxia Xu^1,*, Lei Liu², Jingnan Dong³

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 903-922, 2023, DOI:10.32604/cmes.2023.026627 - 23 April 2023

Abstract In recent years, with the great success of pre-trained language models, the pre-trained BERT model has been gradually applied to the field of source code understanding. However, the time cost of training a language model from zero is very high, and how to transfer the pre-trained language model to the field of smart contract vulnerability detection is a hot research direction at present. In this paper, we propose a hybrid model to detect common vulnerabilities in smart contracts based on a lightweight pre-trained language model BERT and connected to a bidirectional gate recurrent unit model. More >

S. Vijayashaarathi^1,*, S. NithyaKalyani²

Computer Systems Science and Engineering, Vol.46, No.3, pp. 2881-2897, 2023, DOI:10.32604/csse.2023.036864 - 03 April 2023

Abstract In recent years, real-time video streaming has grown in popularity. The growing popularity of the Internet of Things (IoT) and other wireless heterogeneous networks mandates that network resources be carefully apportioned among versatile users in order to achieve the best Quality of Experience (QoE) and performance objectives. Most researchers focused on Forward Error Correction (FEC) techniques when attempting to strike a balance between QoE and performance. However, as network capacity increases, the performance degrades, impacting the live visual experience. Recently, Deep Learning (DL) algorithms have been successfully integrated with FEC to stream videos across multiple… More >

Po-Yuan Yang^1,*, Yu-Cheng Liao², Fu-I Chou²

Computer Systems Science and Engineering, Vol.46, No.3, pp. 2861-2880, 2023, DOI:10.32604/csse.2023.036810 - 03 April 2023

Abstract Aquaculture has long been a critical economic sector in Taiwan. Since a key factor in aquaculture production efficiency is water quality, an effective means of monitoring the dissolved oxygen content (DOC) of aquaculture water is essential. This study developed an internet of things system for monitoring DOC by collecting essential data related to water quality. Artificial intelligence technology was used to construct a water quality prediction model for use in a complete system for managing water quality. Since aquaculture water quality depends on a continuous interaction among multiple factors, and the current state is correlated… More >

Ping-Huan Kuo^1,2, Yu-Tsun Chen¹, Her-Terng Yau^1,2,*

Computer Systems Science and Engineering, Vol.46, No.3, pp. 2687-2709, 2023, DOI:10.32604/csse.2023.036293 - 03 April 2023

Abstract The power factor is the ratio between the active and apparent power, and it is available to determine the operational capability of the intended circuit or the parts. The excitation current of the synchronous motor is an essential parameter required for adjusting the power factor because it determines whether the motor is under the optimal operating status. Although the excitation current should predict with the experimental devices, such a method is unsuitable for online real-time prediction. The artificial intelligence algorithm can compensate for the defect of conventional measurement methods requiring the measuring devices and the… More >