수요 특성이 계층적 수요예측법의 퍼포먼스에 미치는 영향 : 해군 수리부속 사례 연구
The Impact of Demand Features on the Performance of Hierarchical Forecasting : Case Study for Spare parts in the Navy
The demand for naval spare parts is intermittent and erratic. This feature, referred to as non-normal demand, makes forecasting difficult. Hierarchical forecasting using an aggregated time series can be more reliable to predict non-normal demand than direct forecasting. In practice the performance of hierarchical forecasting is not always superior to direct forecasting. The relative performance of the alternative forecasting methods depends on the demand features. This paper analyses the influence of the demand features on the performance of the alternative forecasting methods that use hierarchical and direct forecasting. Among various demand features variability, kurtosis, skewness and equipment groups are shown to significantly influence on the performance of the alternative forecasting methods.
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