Non-hypothetical projection pursuit regression for the prediction of hydration heat of Portland-cement-based cementitious system
Can Qin,
Jingwei Gong,
Gangchuan Xie,
Jianxin He,
Liang Liu,
Haihua Yang,
Chuanling Deng
Affiliations
Can Qin
College of Hydraulic and Civil Engineering, Xinjiang Agricultural University, Urumqi, Xinjiang, 830052, PR China; Xinjiang Key Laboratory of Hydraulic Engineering Security and Water Disasters Prevention, Urumqi, 830052, PR China
Jingwei Gong
College of Hydraulic and Civil Engineering, Xinjiang Agricultural University, Urumqi, Xinjiang, 830052, PR China; Xinjiang Key Laboratory of Hydraulic Engineering Security and Water Disasters Prevention, Urumqi, 830052, PR China; Corresponding author. College of Hydraulic and Civil Engineering, Xinjiang Agricultural University, Urumqi, Xinjiang 830052, PR China.
Gangchuan Xie
College of Hydraulic and Civil Engineering, Xinjiang Agricultural University, Urumqi, Xinjiang, 830052, PR China; Xinjiang Key Laboratory of Hydraulic Engineering Security and Water Disasters Prevention, Urumqi, 830052, PR China
Jianxin He
College of Hydraulic and Civil Engineering, Xinjiang Agricultural University, Urumqi, Xinjiang, 830052, PR China; Xinjiang Key Laboratory of Hydraulic Engineering Security and Water Disasters Prevention, Urumqi, 830052, PR China
Liang Liu
College of Hydraulic and Civil Engineering, Xinjiang Agricultural University, Urumqi, Xinjiang, 830052, PR China; Xinjiang Key Laboratory of Hydraulic Engineering Security and Water Disasters Prevention, Urumqi, 830052, PR China
Haihua Yang
College of Hydraulic and Civil Engineering, Xinjiang Agricultural University, Urumqi, Xinjiang, 830052, PR China; Xinjiang Key Laboratory of Hydraulic Engineering Security and Water Disasters Prevention, Urumqi, 830052, PR China
Chuanling Deng
College of Mechanical and Electrical Engineering, Xinjiang Agricultural University, Urumqi, Xinjiang, 830052, PR China
In this study, the non-hypothetical projection pursuit regression (NH-PPR) is proposed. The proposed NH-PPR model can predict the hydration heat based on the four cement phases, FA, SL, cement fineness and hydration time. The NH-PPR model is proposed by using the multiple layer iteration method and the non-hypothetical and non-parametric ridge functions to enhance accuracy and solve the problems caused by the parameter selection and the subjective hypothesis. The modeling data set is applied to train model, the testing data set is regressed and fitted into the model, and then the obtained results are compared with the BP model. To further validate the proposed model, another published data set is used to obtain a higher degree of confidence in the prediction. It is shown that the proposed model obtains the better accuracy, stability and versatility, and avoids the parameter selection and subjective hypothesis.
