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Software Forecasting Models

机译:软件预测模型

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Several forecasting models were evaluated with respect to their forecasting accuracy using NASA Space Shuttle failure data. Simple models like exponential smoothing are attractive if the forecasting range can be limited. This is the case because these models use the most recent data in making a forecast. In other cases, where forecasts must be made over a wide range, software reliability models are superior. The reason is that these models use a larger set of data in making parameter estimates. This feature results in more accurate forecasts over a wider range of time periods in the future. We found that significant improvements could be made to forecasting accuracy for all models by the simple process of modifying original ' forecasts based on the relative errors of those forecasts.
机译:使用NASA航天飞机故障数据评估了几种预报模型的预报准确性。如果可以限制预测范围,则像指数平滑这样的简单模型将很有吸引力。之所以如此,是因为这些模型在进行预测时会使用最新数据。在其他情况下,如果必须进行广泛的预测,则软件可靠性模型会更出色。原因是这些模型在进行参数估计时使用了更大的数据集。此功能可以在将来更广泛的时间范围内提供更准确的预测。我们发现,通过基于这些预测的相对误差修改原始预测的简单过程,可以大大改善所有模型的预测准确性。

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