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Predicting the Personal-Best Times of Speed Skaters Using Case-Based Reasoning

机译:使用基于案例的推理预测速度滑雪运动员的个人最佳时间

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Speed skating is a form of ice skating in which the skaters race each other over a variety of standardised distances. Races take place on specialised ice-rinks and the type of track and ice conditions can have a significant impact on race-times. As race distances increase, pacing also plays an important role. In this paper we seek to extend recent work on the application of case-based reasoning to marathon-time prediction by predicting race-times for speed skaters. In particular, we propose and evaluate a number of case-based reasoning variants based on different case and feature representations to generate track-specific race predictions. We show it is possible to improve upon state-of-the-art prediction accuracy by harnessing richer case representations using shorter races and track-adjusted finish and lap-times.
机译:速度滑冰是一种冰滑冰的形式,滑冰者在各种标准化距离上互相竞争。在专门的冰溜冰场上进行比赛,轨道和冰条件的类型可能对竞争时间产生重大影响。随着比赛距离增加,起搏也发挥着重要作用。在本文中,我们寻求通过预测速度滑雪运动员的竞争时间来扩展基于案例的推理到马拉松时间预测的努力。特别是,我们提出并根据不同的情况和特征表示来评估许多基于案例的推理变体,以生成特定于轨迹的种族预测。我们表明可以通过使用更短的比赛和曲目调整的饰面和圈时间来利用更丰富的壳体表示来改善最先进的预测精度。

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