TY  - BOOK
AU  - Xu,Yidong
AU  - Mao,Jianghong
AU  - Zhuge,Weijie
AU  - Yu,Xiaoniu
AU  - Wu,Ping
ED  - SpringerLink (Online service)
TI  - Prediction and Evaluation of Hardened Concrete Strength: Based on Machine Learning and Mixture Composition 
SN  - 9789819682379
AV  - TA1-2040 
U1  - 624 23
PY  - 2026///
CY  - Singapore
PB  - Springer Nature Singapore, Imprint: Springer
KW  - Civil engineering
KW  - Materials
KW  - Civil Engineering
KW  - Materials Engineering
N1  - 1. Introduction -- 2. Raw materials and experimental method -- 3. Establishment of maturity equations for different temperature intervals -- 4. Concrete strength prediction based on artificial neural networks -- 5. Development of intelligent concrete strength program -- 6. Conclusions and foresight -- Appendix; Open Access
N2  - This open access book monitors the development of the temperature field within concrete structures and, based on the Arrhenius equation, constructs F-P maturity equations applicable to different temperature ranges. It investigates the impact of hydration rate on the strength prediction method of the maturity equation. Furthermore, the book employs artificial neural network theory to improve the accuracy of early concrete strength predictions, optimizing the neural network model to develop a more precise and widely applicable prediction model. An intelligent program is developed using MATLAB, facilitating rapid strength prediction and assessment on construction sites using measured parameters
UR  - https://doi.org/10.1007/978-981-96-8237-9
ER  -