Neural expert weighing

摘要

This article describes a novel framework for combining time series forecasts. It uses neural network regression models to estimate, at a given point in time, the linear weights (relevancies) of the available experts (forecasters) at that time. With those weights, the experts can be linearly combined to produce a single, potentially more accurate, forecast. This new weight generation framework was designed to be especially useful for multi-step-ahead forecasting.