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Year: 2022, Volume: 22, Number: 1
... within the dataset is very ‚ The success of Recurrent Neural Networks (RNN) in similar to normal traffic ... A Hybrid Deep Learning Approach for Intrusion Detection in IoT Networks Murat EME‡, Mehmet Hilal -ZCANHAN Department of Computer ... . With increasing mission- every IoT device on the network. Therefore, IoT devices are critical IoT data ...
42. Active Disturbance Rejection Control Applied to a Three-Phase Grid-Connected Photovoltaic System
Year: 2022, Volume: 22, Number: 1
... combined with such as fuzzy logic control FLC, artificial neural network incremental conductance (ADRC_IncCond) is used to ... Decision and Control, 2007, pp. 3501-3506. networks MPPT controller: review, simulation and hardware doi ... 10.1109/CDC.2007.4434676 implementation," Renewable and Sustainable Energy Reviews, vol. [27] S. Shao ...
Year: 2022, Volume: 22, Number: 1
... RiceNet: Processing, vol. 23, pp. 1953-1964, 2014. convolutional neural networks-based model to classify Pakistani doi:10.1109/TIP.2014.2310123 grown rice seed types ... " Multimedia Systems, pp. 1-9, 2021. [14] A. Khurshid, H. Zulfiqar, and H. Muhammad, "Copy-move and doi ...
Year: 2022, Volume: 22, Number: 1
... fed induction doi:10.1109/TPWRD.2012.2195685 generator of variable speed wind turbine system using neural [2] P. Tchakoua, and R. Wamkeue, "A ... p s € ki Vs converter in dq frame, Rg and Lg are the network resistance € 2 pll pll (12) i s € Vs k p ...
Year: 2021, Volume: 21, Number: 4
... of the microgrid within a hybrid method that combines a neural network with a nominal parameters. prediction method based ... irradiance doi:10.1109/CCECE.2017.7946775 forecasting using deep neural networks," Procedia Comput. Sci., vol ... cost optimization of an islanded microgrid [1- distribution network. The authors of [16] proposed an ...
Year: 2021, Volume: 21, Number: 4
... the flight route, there was no significant quadruplet convolutional neural networks," in Proceedings of the difference addition ... the success between windless and IEEE conference on computer vision and pattern recognition, 2017, pp. 5620-5629. ... , M. f. Zhou, "Decentralized PID neural network artificial intelligence," MIT press, 1992. ...
Year: 2021, Volume: 21, Number: 4
... , pp. 33-55, 2019. detection using artificial neural networks," 20th Conf. Open doi: ... ENISA), the recent changes in the cyber computer networks, aiming to band together all the threat landscape ... 21, Number 4, 2021 Machine Learning Enhanced Entropy-Based Network Anomaly Detection Valentina TIMCENKO1,2, Slavko GAJIN1 ...
Year: 2021, Volume: 21, Number: 4
... under electricity markets," to-grid aggregator for frequency regulation," IEEE Transactions on Neural Computing and Applications, vol. 23, no. 7, pp. ... of EVs in be monitored and controlled efficiently [3-4]. Previous the distribution network contributes to the increment of capital works investigated the power aggregator of EV, ...
Year: 2021, Volume: 21, Number: 4
... , M. Niebner, "SG-NN: Sparse Generative Neural constraints for 3D indoor modelling," Automation in ... , Networks for Self-Supervised Scene Completion of RGB-D Scans," vol. 106, pp. 102913.1-102913.21, Oct ... 710048, Xi'an, China 2 Shaanxi Key Laboratory of Network Computing and Security Technology, 710048, Xi'an, ...
Year: 2021, Volume: 21, Number: 4
... model has obvious performance historical data. Therefore, artificial neural network as a advantages, is conducive to the ... , y (2) Compared with other traditional neural networks, the original signal, and ξ represents the ... frequency. LSTM has the ability to learn long-term dependent information, which can deeply explore the complex (b ...
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