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Tianao Qin, Ruixin Chen, Rufu Qin and Yang Yu
Time series prediction is an effective tool for marine scientific research. The Hierarchical Temporal Memory (HTM) model has advantages over traditional recurrent neural network (RNN)-based models due to its online learning and prediction capabilities. G...
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Anthony A. Amori, Olufemi P. Abimbola, Trenton E. Franz, Daran Rudnick, Javed Iqbal and Haishun Yang
Model calibration is essential for acceptable model performance and applications. The Hybrid-Maize model, developed at the University of Nebraska-Lincoln, is a process-based crop simulation model that simulates maize growth as a function of crop and fiel...
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Yanqi Wang, Xinyan Qin, Wenxing Jia, Jin Lei, Dexin Wang, Tianming Feng, Yujie Zeng and Jie Song
In order to improve the flight efficiency of a flying?walking power transmission line inspection robot (FPTLIR) during flight missions, an accurate energy consumption model is constructed, and a multiobjective optimization approach using the improved NSG...
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Mingxin Zou, Yanqing Zhou, Xinhua Jiang, Julin Gao, Xiaofang Yu and Xuelei Ma
Field manual labor behavior recognition is an important task that applies deep learning algorithms to industrial equipment for capturing and analyzing people?s behavior during field labor. In this study, we propose a field manual labor behavior recogniti...
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Zhongda Ren, Chuanjie Liu, Yafei Ou, Peng Zhang, Heshan Fan, Xiaolong Zhao, Heqin Cheng, Lizhi Teng, Ming Tang and Fengnian Zhou
Effectively simulating the variation in suspended sediment concentration (SSC) in estuaries during typhoons is significant for the water quality and ecological conditions of estuarine shoal wetlands and their adjacent coastal waters. During typhoons, SSC...
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