Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 4 of 4
Full-Text Articles in Engineering
Research On The Network Of 3d Smoke Flow Super-Resolution Data Generation, Jinlian Du, Shufei Li, Xueyun Jin
Research On The Network Of 3d Smoke Flow Super-Resolution Data Generation, Jinlian Du, Shufei Li, Xueyun Jin
Journal of System Simulation
Abstract: Aiming at the problem of low data generation efficiency due to the high complexity of solving the N-S equation of smoke flow field, a deep learning model which can generate high-resolution smoke flow data based on low-resolution smoke flow data solved by N-S equation is explored and designed. Based on the Generative Adversarial Network, the smoke data reconstruction network based on the sub voxel convolution layer is constructed. Considering the fluidity of smoke, time loss based on advection step is introduced into the loss function to realize high-precision smoke simulation. By extending the image super-resolution quality evaluation index, the …
Research On Intrusion Detection Based On Stacked Autoencoder And Long-Short Memory, Lin Shuo, An Lei, Zhijun Gao, Shan Dan, Wenli Shang
Research On Intrusion Detection Based On Stacked Autoencoder And Long-Short Memory, Lin Shuo, An Lei, Zhijun Gao, Shan Dan, Wenli Shang
Journal of System Simulation
Abstract: As network attacks increasingly hidden, intelligent and complex. Simple machine learning cannot deal with attacks timely. A deep learning method based on the combination of SDAE and LSTM is proposed. Firstly, the distribution rules of network data are extracted intelligently layer by layer by SDAE, and the diverse anomaly features of high-dimensional data ate extracted by using coefficient penalty and reconstruction error of each coding layer. Then, LSTM’ s memory function and the powerful learning ability of sequence data are used to classify learning depth. Finally, the experiments are carried out with the UNSW-NB15 data set, which is analyzed …
Creating Synthetic Satellite Cloud Data Based On Gan Method, Wencong Cheng, Xiaokang Shi, Zhigang Wang
Creating Synthetic Satellite Cloud Data Based On Gan Method, Wencong Cheng, Xiaokang Shi, Zhigang Wang
Journal of System Simulation
Abstract: To create the synthetic satellite cloud data in the domain of Meteorology, a method based on Generative Adversarial Networks (GAN) is proposed. Depending on ability of the nonlinear mapping and the information extraction of raster data with the deep learning network, a deep generative adversarial network model is proposed to extract the corresponding information between the numerical weather prediction(NWP) products and the satellite cloud data, and then the appropriate elements of the NWP product are chosen as the input to synthesize the corresponding satellite cloud data. The experiments are conducted on the re-analysis products of the European Centre …
Network Traffic Anomaly Detection Method For Imbalanced Data, Shuqin Dong, Bin Zhang
Network Traffic Anomaly Detection Method For Imbalanced Data, Shuqin Dong, Bin Zhang
Journal of System Simulation
Abstract: Aiming at the poor detection performances caused by the low feature extraction accuracy of rare traffic attacks from scarce samples, a network traffic anomaly detection method for imbalanced data is proposed. A traffic anomaly detection model is designed, in which the traffic features in different feature spaces are learned by alternating activation functions, architectures, corrupted rates and dropout rates of stacked denoising autoencoder (SDA), and the low accuracy in extracting features of rare traffic attacks in a single space is solved. A batch normalization algorithm is designed, and the Adam algorithm is adopted to train parameters of …