Optimizing SVM Model as Predicting Model for Sewer Pipes in the Two Main Cities in Colombia

Abstract

As in most of the cities around the world, in the last 30 years Latin-American ones have focused on investing in building infrastructure to provide sewer and water services to the communities. However, these infrastructures are going aging day to day. The municipalities need to extend management activities by the development of support tools such as deterioration models to face the aging problem. In the literature of sewer asset management, SVM has been a useful tool to predict and forecast the structural condition of pipes. In this work, the use of differential evolution method as optimization tool was implemented to find the optimal hyper-parameters for SVM models. The SVM models were applied in the main cities of Colombia (Bogota and Medellin) given as a result that the optimized SVM model provides less than 5% of deviation in the prediction of structural conditions in both cities.