Interval Forecast of Water Quality Parameters
Ohashi Orlando, Luı́s Torgo, Rita P. Ribeiro · Frontiers in artificial intelligence and applications · 2010
The current quality control methodology adopted by the water distribution service provider in the metropolitan region of Porto - Portugal, is based on simple heuristics and empirical knowledge. Based on the domain complexity and data volume, this application is a perfect candidate to apply data mining process. In this paper, we propose a new methodology to predict the range of normality for the values of different water quality parameters. These intervals of normality are of key importance to decide on costly inspection activities. Our experimental evaluation confirms that our proposal achieves good results on the task of forecasting the normal distribution of values for the following 30 days. The proposed method can be applied to other domains with similar network monitoring objectives.