自适应神经模糊推理系统
剪切(地质)
结构工程
推理系统
人工神经网络
计算机科学
抗剪强度(土壤)
岩土工程
工程类
模糊逻辑
地质学
材料科学
人工智能
模糊控制系统
复合材料
土壤科学
土壤水分
作者
Ali Toghroli,Mohammad Mohammadhassani,Meldi Suhatril,Mahdi Shariati,Zainah Ibrahim
出处
期刊:Steel and Composite Structures
[Technopress]
日期:2014-11-25
卷期号:17 (5): 623-639
被引量:184
标识
DOI:10.12989/scs.2014.17.5.623
摘要
Due to recent advancements in the area of Artificial Intelligence (AI) and computational intelligence, the application of these technologies in the construction industry and structural analysis has been made feasible. With the use of the Adaptive-Network-based Fuzzy Inference System (ANFIS) as a modelling tool, this study aims at predicting the shear strength of channel shear connectors in steel concrete composite beam. A total of 1200 experimental data was collected, with the input data being achieved based on the results of the push-out test and the output data being the corresponding shear strength which were recorded at all loading stages. The results derived from the use of ANFIS and the classical linear regressions (LR) were then compared. The outcome shows that the use of ANFIS produces highly accurate, precise and satisfactory results as opposed to the LR.
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