SELECTING PARAMETERS FOR SHORT‐TERM FORECASTING TECHNIQUES
比较了三种参数选择模式对四种短期预测技术误差的影响，并考察历史数据量对预测效果的作用，发现传统单步搜索并非总是最优，增加历史数据可降低误差。
The objective of this paper is to discover which of three forecasting modes used to select parameters for four short‐term forecasting techniques minimizes errors. The study also examines whether the amount of historical data used to find parameters contributes to forecasting success. The results show the traditional one‐ahead search routine works well in some, but not all, forecasting situations. Also, forecasting errors appear to decline when more historical data are included in the parameter search.