Advances in knowledge discovery and data mining
Advances in knowledge discovery and data mining
Parameterisation and evaluation of a Bayesian network for use in an ecological risk assessment
Environmental Modelling & Software
Multivariate statistical monitoring of continuous wastewater treatment plants
Engineering Applications of Artificial Intelligence
Knowledge Discovery in a Wastewater Treatment Plant with Clustering Based on Rules by States
Proceedings of the 2007 conference on Artificial Intelligence Research and Development
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Often, dynamic patterns are constructed from the concatenation of the patterns identified on each state of the process. In this work it is shown that the interpretation of dynamic patterns can not be constructed as a simple concatenation of the concepts associated to the components of the dynamic process. This phenomenon is defined as a Paradox of the Mitigant Trajectories (PTM). A method to identify PTM's is proposed as well as a method to correct them. Also, the proposal is applied to a Wastewater Treatment Plant (WWTP). The correct interpretation of dynamic patterns is crucial as inducted knowledge to be considered for an input to Intelligent Environmental Decision Support Systems (IEDSS).