Using Wavelets to Identify Linear Dynamic Models
Abstract
The forecasting process of water cleaning in the city of Mosul was studied using the input and output variables represented by some tests performed on raw water before the filtration process, to be treated through multiple filtration stages. To determine the safety of water for human consumption, the filtration process was studied by forecasting using Dynamic models, including the self-regression model with additional inputs, the moving averages model, self-regression with additional inputs, as well as the output error model and the box Jenkins model. the best model obtained from the data was diagnosed using statistical criteria, and then a comparison was made to predict through forecasting criteria and applied to water data.
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