Arup Dey, Nita Yodo, Om P. Yadav, Ragavanantham Shanmugam and Monsuru Ramoni
Data-driven algorithms have been widely applied in predicting tool wear because of the high prediction performance of the algorithms, availability of data sets, and advancements in computing capabilities in recent years. Although most algorithms are supp...
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Shuo Wang, Kailun Feng and Yaowu Wang
In construction planning, decision making has a great impact on final project performance. Hence, it is essential for project managers to assess the construction planning and make informed decisions. However, disproportionately large uncertainties occur ...
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Yu Du, Ting Xu, Yuzhang Che, Bifeng Yang, Shaojie Chen, Zhikun Su, Lianxia Su, Yangruixue Chen and Jiafeng Zheng
The mesoscale Weather Research and Forecasting (WRF) model has been widely employed to forecast day-ahead rainfalls. However, the deterministic predictions from the WRF model incorporate relatively large errors due to numerical discretization, inaccuraci...
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Junkai Wang, Lianlei Lin, Zaiming Teng and Yu Zhang
With the exponential growth in the amount of available data, traditional meteorological data processing algorithms have become overwhelmed. The application of artificial intelligence in simultaneous prediction of multi-parameter meteorological data has a...
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Kecen Li, Haopeng Zhang and Chenyu Hu
Estimation of spacecraft pose is essential for many space missions, such as formation flying, rendezvous, docking, repair, and space debris removal. We propose a learning-based method with uncertainty prediction to estimate the pose of a spacecraft from ...
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