中文摘要：

对在线模型进行扩展，允许决策者提供预测并从中受益，即使预测失败，决策者也能控制风险，使得在线算法的性能相对于最优离线算法不会太差。研究分析了两种典型预测，第一种下方预测，即价格将会下降到某水平，第二种上方预测，即价格绝对不会下降到某水平。针对不同的预测设计不同的算法，并通过竞争分析的方法得到相应的竞争比。还考虑了在整个购买过程中允许进行多次预测情形，并进行敏感性分析。

英文摘要：

The online model is extended to allow decision-makers to predict and benefit from it. Even if the forecast fails, decision-makers can control the risk and make the performance of the online algorithm is not too bad relative to the optimal offline algorithm. Two typical forecast models are considered in this research. The first model is below forecast, i.e. the price will drop to a certain level The second model is above predict, i. e. the price will not drop to a certain level. Different algorithms are designed in allusion to different predictions, and the corresponding competitive ratios are gained by the competitive analysis method. The scenario of forecasting for several times allows in the entire purchase process and sensibility analysis is made.