Neural networks for evaluating workability of high-performance concrete(以類神經網路評估高性能混凝土的工作度)

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Title:	Neural networks for evaluating workability of high-performance concrete(以類神經網路評估高性能混凝土的工作度)
Authors:	葉怡成 Yeh, I-Cheng
Contributors:	資訊管理學系 Information Management
Keywords:	高性能混凝土;強塑劑;坍流度;工作度;類神經網路 high-performance;neural networks
Date:	2007
Issue Date:	2014-06-27 01:49:25 (UTC+8)
Abstract:	本研究建立類神經網以探索類神經網路預測高性能混凝土坍流度的可行性。以訓練過的類神經網路進行混凝土坍流度的計算模擬。用變化因子的組合，像水膠比、SP/膠結料比、用水量，達到變化混凝土坍流度的效果，產生了坍流度曲線，以探索水膠比、SP/膠結料比、用水量的作用。結果發現 (1) 以類神經網路預測混凝土坍流度很有潛力；(2) 在水膠比分別為0.4和0.5下，每增加百分之一的SP/膠結料比，可節省的用水量約為15和10 ；(3) 增加SP/膠結料比增加了坍流度，然而其效果在高水膠比時遠比低水膠比時來得小。 In this study, an artificial neural network was established to explore the feasibility of using neural networks in predicting the slump-flow of concrete. Computational simulation of concrete slump-flow was performed using the trained neural network. The v
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