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Yufei Wang, Honghai Zhang, Zongbei Shi, Jinlun Zhou and Wenquan Liu
General aviation accidents have complex interactions and influences within them that cannot be simply explained and predicted by linear models. This study is based on chaos theory and uses general aviation accident data to conduct research on different t...
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Xingkui Xu, Chunfeng Wu, Qingyu Hou and Zhigang Fan
As an important angle sensor of the opto-electric platform, gyro output accuracy plays a vital role in the stabilization and track accuracy of the whole system. It is known that the generally used fixed-bandwidth filters, single neural network models, or...
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Xingkui Xu, Chunfeng Wu, Qingyu Hou and Zhigang Fan
As an important angle sensor of the opto-electric platform, gyro output accuracy plays a vital role in the stabilization and track accuracy of the whole system. It is known that the generally used fixed-bandwidth filters, single neural network models, or...
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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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Yicheng Gong, Zhongjing Wang, Guoyin Xu and Zixiong Zhang
The reliable and accurate prediction of groundwater levels is important to improve water-use efficiency in the development and management of water resources. Three nonlinear time-series intelligence hybrid models were proposed to predict groundwater leve...
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Zhengyan Cui, Junjun Zhang, Giseop Noh and Hyun Jun Park
Traffic prediction is a popular research topic in the field of Intelligent Transportation System (ITS), as it can allocate resources more reasonably, relieve traffic congestion, and improve road traffic efficiency. Graph neural networks are widely used i...
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Mina Tadros, Roberto Vettor, Manuel Ventura and Carlos Guedes Soares
This study presents a practical optimization procedure that couples the NavCad power prediction tool and a nonlinear optimizer integrated into the Matlab environment. This developed model aims at selecting a propeller at the engine operating point with m...
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Nancy Arana-Daniel
In recent years, the field of complex, hypercomplex-valued and geometric Support Vector Machines (SVM) has undergone immense progress due to the compatibility of complex and hypercomplex number representations with analytic signals, as well as the power ...
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Due to the nonlinear and non-stationary characteristics of the carbon price, it is difficult to predict the carbon price accurately. This paper proposes a new novel hybrid model for carbon price prediction. The proposed model consists of an extreme-point...
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Yuqi Liu, Chao Sun and Shouda Jiang
To construct an online kernel adaptive filter in a non-stationary environment, we propose a randomized feature networks-based kernel least mean square (KLMS-RFN) algorithm. In contrast to the Gaussian kernel, which implicitly maps the input to an infinit...
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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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Yagang Zhang, Jingyun Yang, Kangcheng Wang and Zengping Wang
This paper considers the effect of nonlinear atmospheric disturbances on wind power prediction. A Lorenz system is introduced as an atmospheric disturbance model. Three new improved wind forecasting models combined with a Lorenz comprehensive disturbance...
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Lan Luo, Yanjun Zhang, Wenxun Dong, Jinglin Zhang and Liping Zhang
Water quality prediction is an important part of water pollution prevention and control. Using a long short-term memory (LSTM) neural network to predict water quality can solve the problem that comprehensive water quality models are too complex and diffi...
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Enhua Cao, Tengfei Bao, Chongshi Gu, Hui Li, Yongtao Liu and Shaopei Hu
Accurate and reliable prediction of dam deformation (DD) is of great significance to the safe and stable operation of dams. In order to deal with the fluctuation characteristics in DD for more accurate prediction results, a new hybrid model based on a de...
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Mergani A. Khairalla, Xu Ning, Nashat T. AL-Jallad and Musaab O. El-Faroug
In the real-life, time-series data comprise a complicated pattern, hence it may be challenging to increase prediction accuracy rates by using machine learning and conventional statistical methods as single learners. This research outlines and investigate...
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Xuehua Zhao, Xu Chen, Yongxin Xu, Dongjie Xi, Yongbo Zhang and Xiuqing Zheng
Accurate forecasting of annual runoff is necessary for water resources management. However, a runoff series consists of complex nonlinear and non-stationary characteristics, which makes forecasting difficult. To contribute towards improved prediction acc...
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Xuehua Zhao, Xu Chen, Yongxin Xu, Dongjie Xi, Yongbo Zhang, Xiuqing Zheng
Pág. 1 - 17
Accurate forecasting of annual runoff is necessary for water resources management. However, a runoff series consists of complex nonlinear and non-stationary characteristics, which makes forecasting difficult. To contribute towards improved prediction acc...
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Saad Sh. Sammen, Mohammad Ehteram, Zohreh Sheikh Khozani and Lariyah Mohd Sidek
Predicting reservoir water levels helps manage droughts and floods. Predicting reservoir water level is complex because it depends on factors such as climate parameters and human intervention. Therefore, predicting water level needs robust models. Our st...
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Lingxiang Wei, Dongjun Guo, Zhilong Chen, Jincheng Yang and Tianliu Feng
Rational use of urban underground space (UUS) and public transportation transfer underground can solve urban traffic problems. Accurate short-term prediction of passenger flow can ensure the efficient, safe, and comfortable operation of subway stations. ...
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Henri Pörhö, Jani Tomperi, Aki Sorsa, Esko Juuso, Jari Ruuska and Mika Ruusunen
The aim of wastewater treatment plants (WWTPs) is to clean wastewater before it is discharged into the environment. Real-time monitoring and control will become more essential as the regulations for effluent discharges are likely to become stricter in th...
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