Evaluation and Application of Ensemble AI-based Models for Estimating Piezometric Heads of Earth Fill Dam

Document Type : Original Article

Authors

Department of Water Resources Engineering, Faculty of Civil Engineering, University of Tabriz, Tabriz, Iran

Abstract

Failure of earth fill dams is a great challenge in Civil Engineering, in which one of the main causes is uncontrolled seepage through the core and foundation of the dam. Thus seepage analysis is one of the most important complications in design, construction and operation of this type of dams; in this way, inspecting the piezometric heads is the first step in seepage analysis. In the following paper, Sattarkhan earth fill dam piezometric heads have been analyzed via Artificial Intelligence (AI) models and a classic black box model, based on two scenarios. Each scenario has different input combinations for modeling of various conditions. To continue ensemble models have been formed via outputs of the single black box models to improve modeling performance. Three methods of model ensemble were considered, including simple linear averaging model, weighted linear averaging model and non-linear neural ensemble model. Results show that employing model ensemble and in particular non-linear ensemble by neural network, improve the modeling accuracy up to 10%. Moreover, by comparison the both scenarios, it is concluded that in case of a failure of a piezometer, employing scenario 2 can be an effective way.

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