近年來類神經網路已廣泛應用在時間數列預測問題上，實證的結果也指出類神經網路為一具有潛力的預測工具。本文旨在闡述類神經網路於時間數列預測課題上的發展趨勢，相關課題按其流程特性分成五個子課題：模式選擇、資料轉換與編輯、樣本選取、輸入變數、網路結構。我們重點式闡述每個課題的工作內容以及類神經網路在各個子課題上的發展現況，文末提供各子課題的未來發展方向以為參考。

CdArtificial Neural Networks have been successfully applied on time series forecasting problems in recent years. This paper aims to addrss the issues of applying Artificial Neural Networks on time series forecasting problems and introduce its current trend in the literature. We first divide the forecasting task into five sub-tasks including model selection, data transformation and editing, instance selection, input selection and network structures. Then the content of each sub-task is briefed, and the recent development of each sub-task is provided correspondingly. Future topics of each sub-task are also rendered.