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Hui Sheng, Min Liu, Jiyong Hu, Ping Li, Yali Peng and Yugen Yi
Time-series data is an appealing study topic in data mining and has a broad range of applications. Many approaches have been employed to handle time series classification (TSC) challenges with promising results, among which deep neural network methods ha...
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Christoph Walter Senn and Itsuo Kumazawa
Noise of any kind can be an issue when translating results from simulations to the real world. We suddenly have to deal with building tolerances, faulty sensors, or just noisy sensor readings. This is especially evident in systems with many free paramete...
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Hideki Ogawa and Yasutake Takahashi
Reservoir computing refers to a computational framework based on recurrent neural networks that can process time-series data. In an echo state network (ESN), which is a type of reservoir computing framework, the reservoir consists of a recursive network ...
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Carmine Guida, Ming Zhang and Juan Shan
Osteoarthritis (OA) is the most common form of arthritis and can often occur in the knee. While convolutional neural networks (CNNs) have been widely used to study medical images, the application of a 3-dimensional (3D) CNN in knee OA diagnosis is limite...
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Daniel Silva Campos, Yara de Souza Tadano, Thiago Antonini Alves, Hugo Valadares Siqueira, Manoel Henrique de Nóbrega Marinho
Pág. e48203
Air pollution is a relevant issue studied worldwide, and its prediction is important for social and economic management. Linear multivariate regression models (LMR) and artificial neural networks (ANN) are widely applied to forecasting concentrations of ...
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Ye Tian, Yue-Ping Xu, Zongliang Yang, Guoqing Wang and Qian Zhu
This study applied a GR4J model in the Xiangjiang and Qujiang River basins for rainfall-runoff simulation. Four recurrent neural networks (RNNs)?the Elman recurrent neural network (ERNN), echo state network (ESN), nonlinear autoregressive exogenous input...
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