Abstract
Artificial neural network (ANN) applications have become popular in the field of water treatment process for modelling and control purposes. This is due to the fact that the processes are not well understood and also due to the large amounts of data available which are recorded for regulatory purposes. Development of such ANN applications are made more difficult by the data handling issues. It is often advantageous to try techniques developed on different plant data sets, under different operating conditions etc, but this is difficult to achieve efficiently in software. In this research, however, we have described several different applications of ANNs to demonstrate the significant results which may be achieved. But more importantly we have shown how the ANN application development, modification, comprehensive testing and benchmarking can be efficiently completed.
To simplify the presentation, we have omitted a section on neural network architectures and learning processes since this is adequately covered in the paper by Renotte et al included as part of this Special Feature.