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自我學習神經網路於多目標建築機能配置最適化之研究

The Optimal Study of Using Self-Learning Neural Network in Multi-Objective Architectural Function Layout

摘要


本研究以管理科學角度,將建築機能配置問題公式化為多目標組合最適化問題,並以「醫院診療大樓多目標機能配置」問題作個案應用。由於問題具多目標與組合爆炸的特性,為此本文先以二元型自我學習神經網路求解問題最佳解,再與隨機解作解答品質及求解效率比較。經測試得到本法解答的成果,遠優於隨機搜索的方法,以作為未來建築規劃相關人員,應用輔助參考之用。

並列摘要


This research is intended to formulate the problem of architectural function layout on the optimal problem of multi-objective combination and takes ”Multi-Objective Architectural Function Layout of Comprehensive Hospital Building” as a case study. Because of its multi-objective and combining explosive characteristics, the problem is solved by using 2-type self-learning neural network in this study. The random researching method is applied in resolving the problem and the results are also made comparison with the solution-quality and solving-efficiency. It is found that the testing results of self-learning neural network are superior to those of random researching method. The proposed result is useful for its application on architectural planning in the further.

參考文獻


邱茂林(1996)。電腦輔助建築設計之研究探討。建築學報。16,115-128。
王敏順(1997)。多目標規劃方法對建築平面之分析。建築學報。21,91-100。
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許志義(1994)。多目標決策。台北:五南圖書出版公司。
謝潮儀(1983)。計量方法與都市土地使用模型。台北:茂榮圖書公司。

被引用紀錄


林長平(2007)。滿足安全性需求之工程設施配置模式〔碩士論文,淡江大學〕。華藝線上圖書館。https://doi.org/10.6846/TKU.2007.00213
陳怡均(2008)。粒子群演算法應用於製造設施佈置之研究〔碩士論文,國立臺北科技大學〕。華藝線上圖書館。https://www.airitilibrary.com/Article/Detail?DocID=U0006-1607200813385000

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