과제정보
본 연구는 국토교통부/국토교통과학기술진흥원의 지원으로 수행되었음(과제번호 21CTAP-C163910-01)
참고문헌
- NARS (2020), The Status and future tasks of old buildings, National Assembly Research Service.
- Park, B., Kim, D., and Park, D.-W. (2020), Predictive System for Unconfined Compressive Strength of Lightweight Treated Soil(LTS) Using Deep Learning, Journal of the Korea Institute for Structural Maintenance and Inspection, 24(3), 18-25. https://doi.org/10.11112/JKSMI.2020.24.3.18
- Eskandari-Naddaf, H., and Kazemi, R. (2017), ANN Prediction of Cement Mortar Compressive Strength, Influence of Cement Strength Class, Construction and Building Materials, 138, 1-11. https://doi.org/10.1016/j.conbuildmat.2017.01.132
- Tenza-Abril, A. J., Villacampa, Y., and Solak, A. M. (2018), Prediction and Sensitivity Analysis of Compressive Strength in Segregated Lightweight Concrete Based on Artificial Neural Network Using Ultrasonic Pulse Velocity, Construction and Building Materials, 189, 1173-1183. https://doi.org/10.1016/j.conbuildmat.2018.09.096
- Onyari, E. K., and Ikotun, B. D. (2018), Prediction of Compressive and Flexural Strengths of a Modified Zeolite Additive Mortar Using Artificial Neural Network, Construction and Building Materials, 187, 1232-1241. https://doi.org/10.1016/j.conbuildmat.2018.08.079
- Ashrafian, A., Taheri Amiri, M. J., and Rezaie-Balf, M. (2018), Prediction of Compressive Strength and Ultrasonic Pulse Velocity of Fiber Reinforced Concrete Incorporating Nano Silica Using Heuristic Regression Methods, Construction and Building Materials, 190, 479-494. https://doi.org/10.1016/j.conbuildmat.2018.09.047
- Cascardi, A., Micelli, F., and Aiello, M. A. (2017), An Artificial Neural Networks Model for the Prediction of the Compressive Strength of FRP-Confined Concrete Circular Columns, Engineering Structures, 140, 199-208. https://doi.org/10.1016/j.engstruct.2017.02.047
- Basyigit, C., Comak, B., and Kilincarslan, S. (2012), Assessment of Concrete Compressive Strength by Image Processing Technique, Construction and Building Materials, 37, 526-532. https://doi.org/10.1016/j.conbuildmat.2012.07.055
- Dogan, G., Arslan, M. H., and Ceylan, M. (2017), Concrete Compressive Strength Detection Using Image Processing Based New Test Method, Measurement: Journal of the International Measurement Confederation, 109, 137-148. https://doi.org/10.1016/j.measurement.2017.05.051
- Dogan, G., Arslan, M. H., and Ceylan, M. (2015), Statistical Feature Extraction Based on an Ann Approach for Estimating the Compressive Strength of Concrete, Neural Network World, 25(3), 301-318. https://doi.org/10.14311/NNW.2015.25.016
- Geron, A. (2017), Hands-On Machine Learning with Scikit-Learn & TensorFlow, O'Reilly Media, Inc, California, 336-339.
- KS F 2405 Standard test method for compressive strength of concrete.