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Nov, 2019
深度续订过程在间歇性需求预测中的应用
Intermittent Demand Forecasting with Deep Renewal Processes
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Ali Caner Turkmen, Yuyang Wang, Tim Januschowski
TL;DR
本研究发展了一套集使用循环神经网络和 “深度” 时间点过程范例的模型, 参数化了条件间歇时间和尺寸分布 , 并在离散和连续时间的间歇需求数据上具有实用价值的良好实证发现。
Abstract
intermittent demand
, where demand occurrences appear sporadically in time, is a common and challenging problem in forecasting. In this paper, we first make the connections between
renewal processes
, and a collect
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