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Deng Xin Yuan on Muck Rack

Deng Xin Yuan

As seen in: Taylor & Francis Online, Pinkbike
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Articles

Research on TCN-Attention-LSTM mechanical drilling rate prediction based on IPO algorithm optimization

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By Wang Chen, Deng Xin Yuan, He Shiming, Wang Hanchang
| Taylor & Francis Online
ABSTRACT Rate of Penetration (ROP) is critical for measuring drilling efficiency, and its accurate prediction boosts drilling performance and cuts costs. Traditional models and single machine learning algorithms are limited by poor hyperparameter optimization and reliance on instantaneous parameters. This study proposes an IPO-optimized TCN-Attention-LSTM model for high-precision dynamic ROP prediction.
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Downhill Racing in China's Gui De Geological Park

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By Scott Rapoport Verified, Deng Xin Yuan
| Pinkbike Verified
China's West is mountainous, vast and visually stunning. The Utah-esque region of Gui De County, located in remote Qinghai province, is home to one of the country's most unique landscapes. Situated on the north-eastern portion of the Qinghai-Tibetan plateau, the Gui De National Geological Park offers some ideal terrain for downhill mountain biking. On August 24th, the park hosted its third Gui De TDRY International Downhill Race.
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