Behaviour prediction of a concrete arch dam combining NN and MLR models – Proposal for the 16th ICOLD BW

Abstract

The main purpose of assessment of dam condition, through the use of the infor-mation provided by the monitoring system, is achieved by having up-to-date knowledge of the dam. Early anomalous behaviour detection is expected in order to allow appropriate intervention to correct the situation or to avoid serious consequences. Once a dam is in its operation phase, the assessment of the dam's condition and the interpretation of the dam's behaviour are supported by data-based models, among others, in which the main goal is to predict the actual structural dam behaviour in order to detect a possible deviation from a considered normal pattern. Within the scope of the 16th International Benchmark Workshop on Numerical Analysis of Dams, this paper presents a methodology for the prediction of different measurements based on the com-bination of the results from multiple linear regression and neural network models. The work dis-cusses the advantages and applicability of the methodology to each type of dataset and the im-portance of engineering expertise and on site knowledge when using data-based models. The obtained results show a good model performance for the training period being a valid option for dam engineering activities.