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Haoyu Lin, Pengkun Quan, Zhuo Liang, Dongbo Wei and Shichun Di
In the context of automatic charging for electric vehicles, collision localization for the end-effector of robots not only serves as a crucial visual complement but also provides essential foundations for subsequent response design. In this scenario, dat...
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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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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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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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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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Wei Li
The standard covariance matrix adaptation evolution strategy (CMA-ES) is highly effective at locating a single global optimum. However, it shows unsatisfactory performance for solving multimodal optimization problems (MMOPs). In this paper, an improved a...
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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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