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Data-Driven Approach for Analysis of Performance Indices in Mobile Work Machines

机译:数据驱动方法,用于分析移动工作机器中的性能指标

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This paper presents a data-driven approach for the analysis of performance indices in mobile work machines. Performance analysis and optimisation of mobile work machines has become increasingly important in recent years. The mobile work machine optimisation is performed based on performance measurements. One of the most interesting and potential approach for improving the quality of the performance analysis is the utilisation of Big Data and data-driven analysis methods, such as machine learning. This study utilises a machine learning algorithm, Classification and Regression Trees (CART), in the performance analysis of the mobile work machines. The most significant benefit of the presented method is that it provides a statistical reference of the machine performance for the operators. The method enables operators to compare performance against reference fleet of machines working in similar operating conditions. This feature can lead to more informative and reliable interpretations and analysis of the performance values. The results of this paper demonstrate how the presented method was used to analyse the performance of a mobile work machine fleet.
机译:本文提出了一种数据驱动方法,用于分析移动工作机器中的性能指标。移动工作机器的性能分析和优化近年来越来越重要。基于性能测量执行移动工作机优化。提高性能分析质量的最有趣和潜在方法之一是利用大数据和数据驱动分析方法,例如机器学习。本研究利用机器学习算法,分类和回归树(推车),在移动工作机器的性能分析中。呈现方法的最显着益处是它为运营商提供了机器性能的统计参考。该方法使运营商能够比较在类似操作条件下工作的机器参考车队的性能。此功能可导致更具信息丰富和可靠的解释和对性能值的分析。本文的结果展示了如何使用本方法来分析移动工作机队的性能。

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