English  |  正體中文  |  简体中文  |  Items with full text/Total items : 51258/86283 (59%)
Visitors : 8011488      Online Users : 68
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/94327


    Title: 以類神經網路作鋼筋混凝土結構最佳化設計
    Other Titles: Optimal design of reinforced concrete structures using artificial neural networks
    Authors: 陳志偉;Chen, Chih-wei
    Contributors: 淡江大學土木工程學系碩士班
    高金盛;Kao, Chin-Sheng
    Keywords: 類神經網路;鋼筋混凝土;最佳化設計;artificial neural networks;Reinforced Concrete;Optimal Design
    Date: 2013
    Issue Date: 2014-01-23 14:21:29 (UTC+8)
    Abstract: 在傳統鋼筋混凝土結構設計中,結構尺寸與造型配置等變數一般都是利用以往經驗來設定初始值,例如梁柱長度與斷面型式、尺寸等等,事實上,這些變數之間都是相關的。工程師因設計時間過於倉促,最終設計成果往往未能有效率地使各個變數間發揮其最佳效能。而結構最佳化設計問題屬於具有限制條件、非線性以及離散變數的最佳化問題,傳統最佳化設計方法例如梯度法或線性規畫等方法並不適用於求解此類問題。
    類神經網路法有別於以往傳統方法,是一種平行分散式處理計算模式。其基本的運作原理乃以大量、簡單的處理單元,或稱神經細胞互相連接,藉由整體處理單元對外界輸入訊號的簡單運算來處理資訊,擁有類似於人腦的許多特性及優點。
    本研究主要目的在於將類神經網路法配合交叉驗證法與訓練測試法運用於鋼筋混凝土梁構件、柱構件、梁柱構架等結構成本最少化之最佳化設計,本文亦進一步綜合建立鋼筋混凝土建築結構成本最少化之最佳化設計模式。利用本文之研究成果,可使傳統僅滿足耐震需求的鋼筋混凝土建築結構,進一步達到成本最少化之最佳化設計。
    In the traditional design of reinforced concrete structures, structural variables such as size and shape configurations generally use past experience to set the initial value such as the length, cross-section type and size of beam and column. In fact, these variables are correlated. Due to overly hasty design, the final results designed by engineer often failed to efficiently play the best performance for all structural variables. The optimization designs of structure belong to the constrained, nonlinear and discrete variable optimization problems. The traditional design methods such as optimal gradient method or linear programming are not applicable for solving this type of problem.
    Artificial Neural Networks method is different from the traditional one which is a kind of parallel distributed processing computing model. The basic principle of operation is based on a large but simple processing unit, or called Neuron connected to each other; by using the whole processing unit by the simple arithmetic of the external input signal to process information, which is similar to many features and benefits of human brains.
    Main purpose of this paper lies in the Artificial Neural Networks training with cross-validation method and Train-and-Test method used in reinforced concrete beam members, column members, beams and other structural cost minimization framework of optimal design. The paper has further consolidated to establish the cost minimization of reinforced concrete buildings of structural optimization design patterns. Using the results of this study can make traditional reinforced concrete structure which only meets seismic requirements further achieve cost minimization of the optimal design.
    Appears in Collections:[土木工程學系暨研究所] 學位論文

    Files in This Item:

    File SizeFormat
    index.html0KbHTML180View/Open

    All items in 機構典藏 are protected by copyright, with all rights reserved.


    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - Feedback