Prediction of Blast Furnace Slag Concrete Compressive Strength Using Artificial Neural Networks and Multiple Regression Analysis
Author:
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9018168/9034677/09034920.pdf?arnumber=9034920
Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Deep learning based concrete compressive strength prediction model with hybrid meta-heuristic approach;Expert Systems with Applications;2023-12
2. Optimal boosting method of HPC concrete compressive and tensile strength prediction;Structural Concrete;2023-08-15
3. Runtime-based metaheuristic prediction of the compressive strength of net-zero traditional concrete mixed with BFS, FA, SP considering multiple curing regimes;Asian Journal of Civil Engineering;2023-07-24
4. Predicting compressive strength of high-performance concrete with high volume ground granulated blast-furnace slag replacement using boosting machine learning algorithms;Scientific Reports;2022-06-09
5. An intelligent model for the prediction of the compressive strength of cementitious composites with ground granulated blast furnace slag based on ultrasonic pulse velocity measurements;Measurement;2021-02
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