博碩士論文 109522084 完整後設資料紀錄

DC 欄位 語言
DC.contributor資訊工程學系zh_TW
DC.creator郭同益zh_TW
DC.creatorTong-Yi Kuoen_US
dc.date.accessioned2022-7-19T07:39:07Z
dc.date.available2022-7-19T07:39:07Z
dc.date.issued2022
dc.identifier.urihttp://ir.lib.ncu.edu.tw:444/thesis/view_etd.asp?URN=109522084
dc.contributor.department資訊工程學系zh_TW
DC.description國立中央大學zh_TW
DC.descriptionNational Central Universityen_US
dc.description.abstract時間序列資料的大致走向通常稱之為「趨勢線」,然而趨勢線未有精準描述的定義,每個人心中對趨勢線的形狀認知有些許差異,難以用一種趨勢線滿足所有人。另外個別使用者可能也不容易清楚敘述其心中的趨勢線樣貌。 本論文提出一個框架讓個別使用者以「手繪」的方式在十張時間序列資料上標出他認定的趨勢線,讓機器學習模型從中學習該使用者心中的趨勢線樣貌,以應用在其他時間序列資料上。zh_TW
dc.description.abstractThe tendency of a time series is usually referred to as a “trend line”. However, the precise definition of a trend line is still ambiguous. Given a time series, different users may come up with varying shapes of trend lines – some may prefer smooth lines, while others may hope the trend line responds to local turbulence. Therefore, a single trend line definition is challenging to meet everyone’s needs. Meanwhile, it could be complicated for users to clearly describe the requirements of a trend line in their minds. This thesis proposes a framework to learn the customized trend lines that meet users’ demands. First, the framework asks users to plot the expected trend lines on ten time-series datasets. The framework then learns users’ preferred shapes and automatically draws the customized trend lines for other time-series datasets.en_US
DC.subject時間序列zh_TW
DC.subject小樣本zh_TW
DC.subject趨勢線zh_TW
DC.subject時間序列預測zh_TW
DC.subjecttime seriesen_US
DC.subjectsmall sampleen_US
DC.subjecttrend lineen_US
DC.subjecttime series predictionen_US
DC.title針對個別使用者從其少量趨勢線樣本生成個人化趨勢線zh_TW
dc.language.isozh-TWzh-TW
DC.titleGenerating Personalized Trend Line Based on Few Labelings from One Individualen_US
DC.type博碩士論文zh_TW
DC.typethesisen_US
DC.publisherNational Central Universityen_US

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