Compressive Strength Evaluation of Fiber-Reinforced High-Strength Self-Compacting Concrete with Artificial Intelligence
المؤلفون المشاركون
Nguyen, Tu T.
Pham Duy, Hoa
Pham Thanh, Tung
Vu, Hoang Hiep
المصدر
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-12، 12ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-10-22
دولة النشر
مصر
عدد الصفحات
12
التخصصات الرئيسية
الملخص EN
This paper describes the application of two artificial intelligence- (AI-) based methods to predict the 28-day compressive strength of fiber-reinforced high-strength self-compacting concrete (FRHSSCC) from its ingredients.
A series of 131 data samples collected from various published literature sources were used for training, validation, and testing models.
Various AI models were developed with different training algorithms and a number of nodes in the hidden layer to obtain the optimal model for the FRHSSCC data.
It is shown that the performances of the artificial neural network (ANN) were better than that of the adaptive neurofuzzy inference system (ANFIS) model.
Specifically, the overall coefficient of determination (R2) of the ANN and ANFIS models was 0.9742 and 0.9584, respectively.
The sensitivity analysis was also conducted with the ANN model to investigate the effects of input parameters on the output.
The results from the sensitivity analysis revealed that the compressive strength of FRHSSCC at 28 days was more sensitive with the changes of water by cement ratio (WCR) parameter and insensitive with varying amounts of fiber (VOF).
Finally, it can be concluded that the application of artificial intelligence shows the great potential in the prediction of compressive strength of FRHSSCC.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Nguyen, Tu T.& Pham Duy, Hoa& Pham Thanh, Tung& Vu, Hoang Hiep. 2020. Compressive Strength Evaluation of Fiber-Reinforced High-Strength Self-Compacting Concrete with Artificial Intelligence. Advances in Civil Engineering،Vol. 2020, no. 2020, pp.1-12.
https://search.emarefa.net/detail/BIM-1121232
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Nguyen, Tu T.…[et al.]. Compressive Strength Evaluation of Fiber-Reinforced High-Strength Self-Compacting Concrete with Artificial Intelligence. Advances in Civil Engineering No. 2020 (2020), pp.1-12.
https://search.emarefa.net/detail/BIM-1121232
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Nguyen, Tu T.& Pham Duy, Hoa& Pham Thanh, Tung& Vu, Hoang Hiep. Compressive Strength Evaluation of Fiber-Reinforced High-Strength Self-Compacting Concrete with Artificial Intelligence. Advances in Civil Engineering. 2020. Vol. 2020, no. 2020, pp.1-12.
https://search.emarefa.net/detail/BIM-1121232
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1121232
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر