基于机器和深度学习算法的钻井工厂交货期估计:一个案例研究

International Conference on Innovative Intelligent Industrial Production and Logistics Pub Date : 1900-01-01 DOI:10.5220/0010655000003062

Alessandro Rizzuto, David Govi, F. Schipani, Alessandro Lazzeri

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摘要

该项目是一个基于机器学习和深度学习算法的真实案例研究，通过比较，可以更清楚地了解哪种程序更适合工业钻井。预测是通过使用业界提供的预处理数据集的算法获得的。报告了每种算法的损失以及SHAP值，以便了解哪些特征对最终预测影响最大。

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Lead Time Estimation of a Drilling Factory with Machine and Deep Learning Algorithms: A Case Study

: This project is presented as a real case-study based on machine learning and deep learning algorithms which are compared for a clearer understanding of which procedure is more suitable to industrial drilling.The predic-tions are obtained by using algorithms with a pre-processed dataset which was made available by the industry. The losses of each algorithm together with the SHAP values are reported, in order to understand which features most inﬂuenced the ﬁnal prediction.

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International Conference on Innovative Intelligent Industrial Production and Logistics

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