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Shun Wang, Jiayan Wang, Zhikang Xu, Ji Wang, Rui Li and Jinliang Dai
The application of titanium alloy in shipbuilding can reduce ship weight and carbon emissions. To solve the problem of titanium alloy forming, the deformation prediction of titanium alloy line heating based on a backpropagation (BP) neural network and sp...
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Zheng Zhao, Jialing Yuan and Luhao Chen
Air Traffic Flow Management (ATFM) delay can quantitatively reflect the congestion caused by the imbalance between capacity and demand in an airspace network. Furthermore, it is an important parameter for the ex-post analysis of airspace congestion and t...
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Amr A. Abd El-Mageed, Ayoub Al-Hamadi, Samy Bakheet and Asmaa H. Abd El-Rahiem
It is difficult to determine unknown solar cell and photovoltaic (PV) module parameters owing to the nonlinearity of the characteristic current?voltage (I-V) curve. Despite this, precise parameter estimation is necessary due to the substantial effect par...
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Yoga Sasmita, Heri Kuswanto and Dedy Dwi Prastyo
Standard time-series modeling requires the stability of model parameters over time. The instability of model parameters is often caused by structural breaks, leading to the formation of nonlinear models. A state-dependent model (SDM) is a more general an...
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Wenxiao Cao, Guoming Li, Hongfei Song, Boyu Quan and Zilu Liu
Water control of grain has always been a crucial link in storage and transportation. The resistance method is considered an effective technique for quickly detecting moisture in grains, making it particularly valuable in practical applications at drying ...
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Siyao Yu, Haoran Bu, Xue Hu, Wancheng Dong and Lixin Zhang
In order to explore the feasibility of rapid non-destructive detection of cotton leaf chlorophyll content during the growth stage, this study utilized hyperspectral technology combined with a feature variable selection method to conduct quantitative dete...
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Yujie Zhang, Lei Zhang, Duo Sun, Kai Jin and Yu Gu
Wind power generation is a renewable energy source, and its power output is influenced by multiple factors such as wind speed, direction, meteorological conditions, and the characteristics of wind turbines. Therefore, accurately predicting wind power is ...
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Xiaying Wang, Yumei Yang, Yuanping Xia, Shuaiqiang Chen and Yulin She
As one of the most developed coastal cities, Shanghai experiences long-term ground surface settlement disasters during urban expansion periods, which has adverse effects on economic development. To date, many studies regarding Shanghai?s ground surface s...
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Liming Lao, Dangkui Du and Pengzhan Chen
This paper proposes a novel prediction model termed the social and spatial attentive generative adversarial network (SSA-GAN). The SSA-GAN framework utilizes a generative approach, where the generator employs social attention mechanisms to accurately mod...
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Jing Han, Junxian Guo, Zhenzhen Zhang, Xiao Yang, Yong Shi and Jun Zhou
Herein, we propose a new method based on Fourier-transform near-infrared spectroscopy (FT-NIR) for detecting impurities in seed cotton. Based on the spectral data of 152 seed cotton samples, we screened the characteristic wavelengths in full-band spectra...
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