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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/70068

    Title: 類神經網路於高層建築設計風載重案例式專家系統之應用
    Other Titles: The Application of Artificial Neural Networks in a Case-Based Design Wind Load Expert System for Tall Buildings
    Authors: 陳冠廷;王人牧;鄭啟明
    Contributors: 淡江大學土木工程學系
    Keywords: 風力頻譜;相似性;輻狀基底函數神經網路;案例式推理;專家系統;wind force spectrum;case-based reasoning;similarity;expert system;radial basis function neural network
    Date: 2008-08
    Issue Date: 2011-10-23 20:45:22 (UTC+8)
    Publisher: 臺北市:中華民國結構工程學會
    Abstract: 本研究將案例式推理和類神經網路應用於風工程領域,建構出一套應用於高層建築設計風載重之案例式專家系統。藉由此系統可提供使用者取得指定建物模型風洞實驗之風力頻譜和風力係數。若是系統中並無相同之案例,將從既有案例中推斷出最相近模型建物之風力頻譜。模擬風力頻譜部份,則是透過輻狀基底函數神經網路將指定案例相似性最高之前若干件案例納入神經網路訓練,並模擬出指定案例之風力頻譜。系統發展上使用的主要資訊技術為,資料庫MS SQL Server 及案例式推理引擎CBR Works 之結合,以及透過FLASH、Java Server Page 把使用者輸入資訊、CBR Works 所搜尋出之案例,及MATLAB Web Server 執行神經網路後之模擬頻譜展示至網頁上。
    This research constructed a case-based design wind load expert system for high-rise buildings using case-based reasoning and ANN. Users can acquire the design wind spectrums and coefficients of a specific target building. If the same case is not in the system, it settles on the most similar one from the existing cases and offers the wind coefficients and spectrums of the similar case. For more accurate design wind loads of the target building (not one of the existing cases), pre-trained RBFNNs (Radial Basis Function Neural Networks) learned from a group of similar ones in the case database can simulate the wind spectrums of the target building. The IT techniques used in the system include combining the database MS SQL Server with the case-based engine CBR Works, and using FLASH and Java Server Page to display users'inputs, CBR Works searching outcomes and MATLAB Web Server simulated wind spectrums.
    Relation: 中華民國第九屆結構工程研討會論文集=Proceedings of The 9th National Conference on Structure Engineering,10頁
    Appears in Collections:[Graduate Institute & Department of Civil Engineering] Proceeding

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