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Regression-Based Stiffness Test for Pallets Based on Sample Period Reduction by Trimming

机译:基于修剪的采样周期减少的基于回归的托盘刚度测试

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This article proposes a regression-based stiffness test for pallets based on sample period reduction by trimming. The deflection data are collected from the stiffness tests for pallets, of which one group is from virgin pallets, produced by a Korean and a European vendor, and the other group is from recycle pallets made by a Korean vendor. The data consist of the test sample in normal as well as high temperature condition. Applying the cumulative sum of residuals (CUSUM) and the likelihood ratio (LR) methods, we identify the exact points of structural breaks, thereby rejecting the time-constancy of regression relationship. Specifically, the regression relationship turns out heavily influenced by the initial period of the tests. We remedy the potential biases stemming from the initial period by trimming the initial period out of the sample. It is shown that forecasting performances are substantially improved by the truncation of the first hour data.
机译:本文提出了一种基于托盘的基于刚度的刚度测试,该测试基于通过修整减少的样本时间。挠度数据是从货盘的刚度测试中收集的,其中一组是由韩国和欧洲供应商生产的原始货盘,另一组是由韩国供应商制造的回收货盘。数据包括正常和高温条件下的测试样品。应用残差的累积总和(CUSUM)和似然比(LR)方法,我们确定结构断裂的确切点,从而拒绝了回归关系的时间常数。具体来说,回归关系受测试初期的影响很大。我们通过从样本中裁剪出初始时段来补救源自初始时段的潜在偏差。结果表明,截断第一个小时的数据可以显着提高预测性能。

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