Machine learning-based compressive strength prediction for concrete: An adaptive boosting approach

• Published in: Construction & building materials Vol. 230; p. 117000
• Main Authors: Feng, De-Cheng, Liu, Zhen-Tao, Wang, Xiao-Dan, Chen, Yin, Chang, Jia-Qi, Wei, Dong-Fang, Jiang, Zhong-Ming
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 10.01.2020
• Subjects: Adaptive boosting; Artificial intelligence; Concrete compressive strength; Machine learning; Prediction; Strong learner; Weak learner; Machine learning; Prediction; Concrete compressive strength; Strong learner; Adaptive boosting; Artificial intelligence; Weak learner

•The AdaBoost algorithm is adopted to predict the compressive strength of concrete.•1030 sets of data is collected to train the model and reaches an accuracy of 98%.•Different algorithms are compared to show the superior of the proposed model.•Key factors and in the AdaBoost and influence of input v...