With the sustainable development of the construction industry, recycled aggregate (RA) has been widely used in concrete preparation to reduce the environmental impact of construction waste. Compressive strength is an essential measure of the performance of recycled aggregate concrete (RAC). In order to understand the correspondence between relevant factors and the compressive strength of recycled concrete and accurately predict the compressive strength of RAC, this paper establishes a model for predicting the compressive strength of RAC using machine learning and hyperparameter optimization techniques. RAC experimental data from published literature as the dataset, extreme gradient boosting (XGBoost), random forest (RF), K-nearest neighbour (KNN), support vector machine regression Support Vector Regression (SVR), and gradient boosted decision tree (GBDT) RAC compressive strength prediction models were developed. The models were validated and compared using correlation coefficients (R2), Root Mean Square Error (RMSE), mean absolute error (MAE), and the gap between the experimental results of the predicted outcomes. In particular, The effects of different hyperparameter optimization techniques (Grid search, Random search, Bayesian optimization-Tree-structured Parzen Estimator, Bayesian optimization- Gaussian Process Regression) on model prediction efficiency and prediction accuracy were investigated. The results show that the optimal combination of hyperparameters can be searched in the shortest time using the Bayesian optimization algorithm based on TPE (Tree-structured Parzen Estimator); the BO-TPE-GBDT RAC compressive strength prediction model has higher prediction accuracy and generalisation ability. This high-performance compressive strength prediction model provides a basis for RAC’s research and practice and a new way to predict the performance of RAC.
As a prominent component of the construction field of sponge cities, ecological concrete is an essential tool to reach the goals of green, low-carbon living and sustainable development. A quantitative summary of the preliminary research on ecological concrete infrastructure in sponge city architecture is needed. Therefore, CiteSpace and VOSviewer were applied to perform a comparative analysis of the number of papers, countries, institutions, core authors, literature co-citations, research hotspots, and future trends in ecological concrete in the sponge city construction industry. The results show that the number of papers on ecological concrete is increasing, the research collaboration between domestic and foreign authors is relatively single, and there is insufficient interdisciplinary integration between institutions and the phenomenon of “relatively independent research.” The number of papers published in the field of ecological concrete construction has been on the rise, reaching more than 100 in each of the last 10 years, with China and the United States contributing more to the scientific output of the field. To meet the needs of global environmental protection and resource conservation, the theme of “promoting comprehensive resource conservation and recycling” will continue in the future, making concrete a feature of green, low-carbon, sustainable development and other areas of environmental protection in the construction field.