Experiences on the Use of R in the Water Sector

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Description

In this study we present some real cases where R has been a key element on building decision support systems related to the water industry. We have used R in the context of automatic water demand forecast, its application to optimal pumping scheduling and building a framework to offer these algorithms as a service (using RInside, Rcpp, MPI, RProtobuf among others) to easily integrate our work on heterogeneous environments. We have used an HPC cluster with R to solve big problems faster. About water demand forecast we used several tools like lineal models, neural networks or tree based method. On short term we included also weather forecast variables. The selection of the method is carried out dynamically (or online) using out-of-sample recent data. The optimal pumping schedule model is loaded with LPSolveAPI package and solved with CBC. We produce nice HTML5 reports of the solutions using googleVis package.

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