Optimizing SVM models as predicting tools for sewer pipes conditions in the two main cities in Colombia for different sewer asset management purposes

Abstract

Currently, sewer utility systems require extending management activities by developing tools, such as deterioration models, to face their aging problem. In the literature on sewer asset management, Support Vector Machines (SVM) have been a useful tool to predict and forecast pipe’s structural conditions. In this paper, the differential evolution method was implemented as an optimization tool for the hyper-parameters combinations to use in SVM-based models for two different management objectives (network and pipe levels). These models were applied to Colombia’s main cities of Bogotá and Medellin, resulting in a less than 6% deviation in the prediction of structural conditions in both cities at a network level. The DE-optimized SVM models at the pipe level show higher percentages of correct predictions in all structural conditions than non-optimized SVM models (conventional SVM model) for specific management objectives. Therefore, the relevance of optimizing the hyper-parameters of SVM models to improve predictions of the structural condition of unspecified sewer assets became apparent.

Keywords:

• Sewer asset management
• Support Vector Machines
• differential evolution method
• optimization

Acknowledgments

Special acknowledgement is also due to EAB (“Empresa de Acueducto de Bogota”) and EPM (“Empresas Públicas de Medellín) for supplying database information used in this research.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This research was done with support from the PROCOL program; a bilateral arrangement between DAAD in Germany (Proposal title: “Development of innovative tools to support efficient sewer asset management strategies in Germany and Colombia) and COLCIENCIAS in Colombia (Colciencias –Pontificia Universidad Javeriana “Contrato de Financiamiento de Recuperación Contingente de Movilidad Internacional No. 646 del 2015” and Project ID: 6725 - PRY ID – 6853- Proposal title: “Herramientas de gestión proactiva de alcantarillados adapatadas a diferentes contextos de gestión patrimonial”), including funding from the German Federal Ministry of Education and Research (BMBF). The authors would like to thank COLCIENCIAS (Departamento Administrativo de Ciencia, Tecnología e Innovación) and PUJ for their financial support of one of themselves in her PhD studies (“Convocatoria 727 del 2015- Apoyo doctorados nacionales”).