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Xiaochuan Sun, Jiahui Gao and Yu Wang
During the deployment of practical applications, reservoir computing (RC) is highly susceptible to radiation effects, temperature changes, and other factors. Normal reservoirs are difficult to vouch for. To solve this problem, this paper proposed a rando...
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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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Yuebing Xu, Jing Zhang, Zuqiang Long, Hongzhong Tang and Xiaogang Zhang
Effective and accurate water demand prediction is an important part of the optimal scheduling of a city water supply system. A novel deep architecture model called the continuous deep belief echo state network (CDBESN) is proposed in this study for the p...
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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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S. Gowrishankar,P. S. Satyanarayana
Pág. pp. 53 - 62
The number of users and their network utilization will enumerate the traffic of the network. The accurate and timely estimation of network traffic is increasingly becoming important in achieving guaranteed Quality of Service (QoS) in a wireless network. ...
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