臺灣博碩士論文加值系統

財務金融的時間序列資料管理，因為資料特性導致的儲存問題與關聯式資料庫的特性與限制，一直以來都不見成效。金融研究人員往往使用特定的資料來從事研究，不但無法保證資料的正確性且費時費力。一旦時間久了，對原先資料的產生過程不復記憶。此外，其他研究者並不知已有人從事相同的研究工作而多費心力，這都顯示知識工作者之間「知識分享」的重要性。且資料的產生過程中，研究者往往難以確定資料本身的存續性。曆法系統的建構，正好給於研究者時間性參考的依據。此外，資料來源的多樣性與資料轉換的問題，都在在困擾著使用者。所以本研究的目的在基於「開放式智慧型計算系統」架構下，發展出一個主從式架構的「時間序列資料管理系統」，來提供研究人員資料的轉換、時間序列資料的建立、管理與查詢的便利與正確性。並利用物件導向分析設計之「統合模式語言」為研究方法，從資料、時間、功能和環境模式四方面來分析設計此系統。利用物件導向的元件獨立、可攜性與再使用性，將時間序列系統發展朝向多平台環境的利用。而最後實際的研究成果，「時間序列資料管理系統」也受到廣大金融研究人員的期望與重視。它更可以被視為將來研究多層式「開放式智慧型計算系統」架構的先趨，提供後續發展的便利。

While the Internet technology and the data availability are rapidly changing, the competition in the investment business becomes intense and increasing. Although the data for financial applications are simple data, the data typically consist of different time series, of which the interrelationships are complex. We were motivated to develop a “Time Series Management System” (TSMS) to support securities investment researchers for their investment decision-makings. The developed TSMS is a knowledge management system featuring with data conversions, time series modeling capabilities, knowledge sharing, computational intelligence, and performance functionalities. We first build up a calendar sub-subsystem for data conversion purposes. We then use the Unified Modeling Language (UML) for data and time modeling. The resulting TSMS, therefore, is a Client/Server architecture under the framework of the proposed OPen Intelligence Computing System (OPICS), which is a component-based with distributed process capabilities.

書頁名 I
論文口試委員審定書 II
授權書 III
中文提要 IV
英文提要 V
誌謝 VI
目錄 VII
表目錄 IX
圖目錄 X
第一章 緒論 1
第二章 時間序列資料在財務金融上之應用 4
2.1時間序列資料的應用 4
2.2時間序列資料的儲存與管理 5
2.3時間序列資料處理架構的運算效能 7
2.4開放式智慧型計算系統的系統研究架構 8
第三章『時間序列資料管理系統』之需求分析與系統規劃 11
3.1物件導向分析與設計 11
3.2資料模式化的需求與系統之規劃目標 13
第四章『時間序列資料管理系統』各子成員的架構與其邏輯設計 17
4.1系統雛形架構 17
4.2系統模式化的需求分析 21
4.2.1資料模式化 21
4.2.2時間模式化 22
4.2.3功能模式化 30
4.2.4環境模式化 32
第五章『時間序列資料管理系統』的建置與實現 33
5.1資料建置方面 34
5.2時間建置方面 39
5.3功能建置方面 45
5.4環境建置方面 49
5.5系統實際建構畫面 51
第六章 結論與未來研究方向 56
參考文獻 59
附錄 62

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