Combination Forecast of Economic Chaos Based on Improved Genetic Algorithm by Yankun Yang

“…This paper optimizes the BP neural network. Finally, the decision tree model and the BP neural network model optimized by the improved genetic algorithm are combined, and the combined model is optimized by the improved GA. …”
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Soil Classification Based on Deep Learning Algorithm and Visible Near-Infrared Spectroscopy by Xueying Li, Pingping Fan, Zongmin Li, Guangyuan Chen, Huimin Qiu, Guangli Hou

“…Under the condition of randomly dividing the calibration set according to the proportion of 1/3 and 1/4, the classification results by convolutional neural network are also better. The aim of this study is to analyze the feasibility of land cover classification with small samples by convolutional neural network and, according to the deep learning algorithm, to explore new methods for rapid, nondestructive, and accurate classification of the land cover.…”
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SurvBeNIM: The Beran-Based Neural Importance Model for Explaining Survival Models by Lev V. Utkin, Danila Y. Eremenko, Andrei V. Konstantinov, Vladimir A. Muliukha

“…Two strategies of using and training the whole neural network implementing SurvBeNIM are proposed. The first one explains a single instance, and the neural network is trained for each explained instance. …”
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Machine Learning ECG Classification Using Wavelet Scattering of Feature Extraction by Heyam A. Marzog, Haider. J. Abd

“…Through wavelet cascades with a neural network, the wavelet scattering transform can yield a translation invariant and deflection depictions of ECG signals. …”
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An Intelligent Fault Detection Method of a Photovoltaic Module Array Using Wireless Sensor Networks by Kuei-Hsiang Chao, Pi-Yun Chen, Meng-Hui Wang, Chao-Ting Chen

“…The experimental results showed that the proposed portable fault diagnosis meter based on the extension neural network for the photovoltaic power generation system possessed a high level of accuracy in fault identification.…”
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Local Media Image Propagation Algorithm and Its Governance in the Age of Artificial Intelligence by Ming Guo, Weichen Jia

“…The advantages and disadvantages of the video recommendation intelligent algorithm based on the BP neural network are analyzed. By comparing different algorithms, it can be seen that the video recommendation accuracy of the BP neural network algorithm based on swarm optimization (FEBP) is 15.8% higher than that of the traditional BP neural network algorithm. …”
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Presentation of Machine Learning Approaches for Predicting the Severity of Accidents to Propose the Safety Solutions on Rural Roads by Mohammad Habibzadeh, Mahmoud Ameri, Hassan Ziari, Neda Kamboozia, Seyede Mojde Sadat Haghighi

“…In this regard, using accident data from 2017 to 2020, the machine learning algorithms, including multiple logistic regression, multilayer perceptron neural network (MLPNN), and radial basis function neural network (RBFNN) models, as well as statistical methods, including Kolmogorov–Smirnov test, Friedman test, and factor analysis, were implemented to determine the contributory factors in the severity of accidents. …”
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Driver Lane-Changing Behavior Prediction Based on Deep Learning by Cheng Wei, Fei Hui, Asad J. Khattak

“…In this paper, a hybrid neural network prediction model based on recurrent neural network (RNN) and fully connected neural network (FC) is proposed to predict lane-changing behavior accurately and improve the prospective time of prediction. …”
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Traffic Flow Prediction Based on Multi-Spatiotemporal Attention Gated Graph Convolution Network by Yun Ge, Jian F. Zhai, Pei C. Su

“…However, most of the existing research methods solving this problem are based on combining the graph convolutional neural network and recurrent neural network for traffic prediction. …”
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Automatic assessment of nailfold capillaroscopy software: a pilot study by Olga Elżbieta Brzezińska, Krzysztof Andrzej Rychlicki-Kicior, Joanna Samanta Makowska

“…The ResNet-34 deep residual neural network was chosen; 10-fold cross-validation with the validation and test set was performed, using the Darknet-YoloV3 state of the art neural network in a GPU-optimized (P5000 GPU) environment. …”
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Implementation of bagging in time series forecasting by Ia. V. Gramovich, D. Yu. Musatov, D. A. Petrusevich

“…Forecasts for the test period obtained by standard, neural network and bagging-based models for some time series are compared in the computational experiment. …”
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PREDICTING USD/ TL EXCHANGE RATE IN TURKEY: THE LONG-SHORT TERM MEMORY APPROACH by Abdul-razak Bawa Yussif, Fatih Mangır, Zeynep Karaçor, Ayten Yağmur

“…In this paper, we apply the Long-Short Term Memory Neural Network to predict the USD/TL exchange rate in Turkey. …”
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Novel Fuzzy Neural Nonsingular Terminal Sliding Mode Control of MEMS Gyroscope by Zhe Wang, Juntao Fei

“…This paper attempts to improve the robustness and rapidity of a microgyroscope sensor by presenting a double-loop recurrent fuzzy neural network based on a nonsingular terminal sliding mode controller. …”
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Comprehensive Analysis of Fault Diagnosis Methods for Aluminum Electrolytic Control System by Jie-jia Li, Xiao-yan Han, Peng Zhou, Xiao-yu Sun, Na Chang

“…The rough neural network gives the results of fault diagnosis. The simulation results verify the feasibility of the method.…”
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ResNet-50-NTS digital painting image style classification based on Three-Branch convolutional attention by Xiaohong Wang, Qian Ye, Lei Liu, Haitao Niu, Bangbang Du

“…Addressing the difficulties and challenges faced by current traditional digital painting image style classification methods, the study enhances the residual neural network model by incorporating a three-branch convolutional attention mechanism. …”
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The Generalization Complexity Measure for Continuous Input Data by Iván Gómez, Sergio A. Cannas, Omar Osenda, José M. Jerez, Leonardo Franco

“…Using a set of trigonometric functions a model that gives a relationship between the size of the hidden layer of a neural network and the complexity is constructed. Finally, we demonstrate the application of the introduced complexity measure, by using the generated model, to the problem of estimating an adequate neural network architecture for real-world data sets.…”
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Deep learning–based resource allocation for secure transmission in a non-orthogonal multiple access network by Miao Zhang, Yao Zhang, Qian Cen, Shixun Wu

“…We propose a deep neural network–based approach to learn to optimize the resource allocations. …”
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Learning the Car-following Behavior of Drivers Using Maximum Entropy Deep Inverse Reinforcement Learning by Yang Zhou, Rui Fu, Chang Wang

“…After clustering the participants into aggressive and conservative groups, the car-following data were used to train the proposed model, a fully connected neural network model, and a recurrent neural network model. …”
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Research on Recommendation Algorithm of Joint Light Graph Convolution Network and DropEdge by Haicheng Qu, Jiangtao Guo, Yanji Jiang

“…Overfitting in a deep neural network leads to low recommendation precision and high loss. …”
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Fault Diagnosis of Subway Traction Motor Bearing Based on Information Fusion under Variable Working Conditions by Yanwei Xu, Weiwei Cai, Tancheng Xie

“…Then, the original signal is processed and extracted by the wavelet packet decomposition, and the normalized feature information is fused by the convolution neural network. Finally, the two-dimensional convolution neural network model is established to diagnose the bearing fault of the metro traction motor under different conditions. …”
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