Prediction and modeling of mechanical properties of concrete modified with ceramic waste using artificial neural network and regression model
- Title
- Prediction and modeling of mechanical properties of concrete modified with ceramic waste using artificial neural network and regression model
- Creator
- Kshirsagar P.R.; Upreti K.; Kushwah V.S.; Hundekari S.; Jain D.; Pandey A.K.; Parashar J.
- Description
- Over two centuries, concrete has been crucial to building. Thus, eco-friendly concrete is being developed. Emulating these tangible traits has recently gained popularity. Ceramic waste concretes mechanical properties were modeled in this study. Ceramic waste percentages ranged from 5 to 20%. Compressive and tensile concrete strengths were modeled. To predict concrete hardness, regression modeling and artificial neural network (ANN) were used. Model performance was evaluated using prediction coefficients and root-mean-square error (RMSE). ANN models outperformed linear prediction with a coefficient for determination (R2) of 0.97. ANN models achieved root-mean-square errors (RMSEs) of 1.22MPa, 1.21MPa, and 1.022MPa after 7, 14, and 28days of retraining, respectively. Linear regression model showed RMSE values of 1.21, 1.32, and 1.27MPa at 7, 14, and 28days, respectively. In determining the compressive and tensile strength, the R2 was 0.70, meanwhile the ANN model achieved 0.87. Given its accuracy in predicting the strength qualities of ceramics cement and structural stiffness, the ANN model presents a promising tool for representing various types of concrete. The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.
- Source
- Signal, Image and Video Processing, Vol-18, No. Suppl 1, pp. 183-197.
- Date
- 2024-01-01
- Publisher
- Springer Science and Business Media Deutschland GmbH
- Subject
- ANN; Compressive strength; LR; Rejected ceramics; Splitting tensile strength
- Coverage
- Kshirsagar P.R., Department of Electronics & amp; Telecommunication Engineering, J D College of Engineering & amp; Management, Nagpur, India; Upreti K., Department of Computer Science, CHRIST (Deemed to Be University), Delhi-NCR, Uttar Pradesh, Ghaziabad, India; Kushwah V.S., School of Computing Science & amp; Engineering, VIT Bhopal University, Bhopal-Indore Highway, Madhya Pradesh, Bhopal, India; Hundekari S., MIT College of Management, MIT ADT University, Loni Kalbhor, Pune, India; Jain D., Department of Computer Science and Engineering, ABES Engineering College, Ghaziabad, India; Pandey A.K., Department of Computer Science and Engineering, ABES Engineering College, Ghaziabad, India; Parashar J., Department of Computer Science and Engineering, Dr. Akhilesh Das Gupta Institute of Engineering and Technology, New Delhi, India
- Rights
- Restricted Access
- Relation
- ISSN: 18631703
- Format
- Online
- Language
- English
- Type
- Article
Collection
Citation
Kshirsagar P.R.; Upreti K.; Kushwah V.S.; Hundekari S.; Jain D.; Pandey A.K.; Parashar J., “Prediction and modeling of mechanical properties of concrete modified with ceramic waste using artificial neural network and regression model,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 24, 2025, https://archives.christuniversity.in/items/show/12966.