S-Space College of Engineering/Engineering Practice School (공과대학/대학원) Dept. of Civil & Environmental Engineering (건설환경공학부) Theses (Master's Degree_건설환경공학부)
User-Friendly Reliable ANN Model for Stability Number of Rock Armors and Tetrapods : 실무자들을 위한 신뢰성 있는 사석 및 테트라포드 피복재의 안정수 인공신경망 모델
- 공과대학 건설환경공학부
- Issue Date
- 서울대학교 대학원
- Tetrapod ; armor stone ; rock armor ; stability number ; machine learning ; artificial neural networks ; assessment of the reliability ; confidence interval
- 학위논문 (석사)-- 서울대학교 대학원 : 공과대학 건설환경공학부, 2018. 2. 황진환.
- The stability number of rubble mound breakwaters determines the appropriate weight of armor units of concrete or rock required to resist the wave condition. Therefore, the prediction of suitable stability number is necessary for the stability of the breakwaters. Many empirical formulas have been developed for the stability number since Hudson (1959). To improve the empirical formulas which had significant differences between observed data and prediction data, the machine learning, ANN in particular, has been used during the last two decades. However, most of ANN models did not deal with reliability assessment such as confidence interval. In addition, they are seldom used by practicing engineers probably because most of them did not provide them with an explicit calculation method. In this study, to solve these problems, bootstrap resampling technique was used to make the information or assessment of the reliability in prediction. Also, Excel files made with the by-products of the ANN model such as weights and biases are provided, so that practicing engineers can easily use ANN model.