DATA MINING APPLICATION IN PREDICTING CRYPTOSPORIDIUM SPP. OOCYSTS AND GIARDIA SPP. CYSTS CONCENTRATIONS IN RIVERS

Data mining is a set of computer-assisted techniques designed to automatically mine large volumes of integrated data for new, hidden or unexpected information, or patterns. Two artificial neural networks (ANN) models were developed for prediction of Cryptosporidium oocysts and Giardia cysts respectively using multiple water quality parameters as input. These neural models were feed forward networks, trained by back propagation algorithm. Eight water quality parameters were used to predict Cryptosporidium peak concentration and seven parameters were used to model Giardia concentration in Kano River, Nigeria. The ANN models correctly predicted oocysts and cysts concentration with accuracy of 90% and 92% respectively. The neural network model gave excellent results.