Tên bài báo:

Improvement of ANFIS Model for Prediction of Compressive Strength of Manufactured Sand Concrete
Tác giả:
Lý Hải Bằng
Tham gia cùng:
Đào Văn Đông
Phạm Thái Bình
Tạp chí:
Applied Sciences (Switzerland)
Năm xuất bản:
Từ trang 1 đến trang 18
Lĩnh vực:
Kỹ thuật xây dựng công trình giao thông
Phạm vi:
Quốc tế

Tóm tắt:

Use of manufactured sand to replace natural sand is increasing in the last several decades. This study is devoted to the assessment of using Principal Component Analysis (PCA) together with Teaching-Learning-Based Optimization (TLBO) for enhancing the prediction accuracy of individual Adaptive Neuro Fuzzy Inference System (ANFIS) in predicting the compressive strength of manufactured sand concrete (MSC). The PCA technique was applied for reducing the noise in the input space, whereas, TLBO was employed to increase the prediction performance of single ANFIS model in searching the optimal weights of input parameters. A number of 289 configurations of MSC were used for the simulation, especially including the sand characteristics and the MSC long-term compressive strength. Using various validation criteria such as Correlation Coefficient (R), Root Mean Squared Error (RMSE), and Mean Absolute Error (MAE), the proposed method was validated and compared with several models, including individual ANFIS, Artificial Neural Networks (ANN) and existing empirical equations. The results showed that the proposed model exhibited great prediction capability compared with other models. Thus, it appeared as a robust alternative computing tool or an efficient soft computing technique for quick and accurate prediction of the MSC compressive strength

Từ khóa:

manufactured sand concrete adaptive neuro fuzzy inference system compressive strength compressive strength mixture proportion principal component analysis
Thông tin tác giả
Lý Hải Bằng

Lý Hải Bằng

Tiến sĩ

Lý lịch khoa học