MASPLAS '07
Predicting Water Quality in Northwest Indiana
Carl Summers, Joseph Robertson, Brian Hunter, Zhe Wei Wang, Ruijian Zhang
The Northwest Indiana area has historically been a highly industrialized region
and remains so today. However, with rising population levels it has become of
crucial importance that we develop real-time techniques for responsible
management of local resources. This is especially important in terms of the
region's water quality. Newly developed techniques in machine learning are
showing promise in providing alternatives to existing, traditional, mechanistic
modeling practices. In particular the algorithm, implemented by C5, shows
considerable potential as a decision tree modeling tool for water quality
prediction and assessment. This study aims to examine the C5 software and its
prospective use as a real-time system for water quality prediction.
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