Artificial Neural Networks
A Laboratory Investigation
Anil Rahman
Corresponding
Technical University of Munich
Akira Aziz
University of Manchester Institute of Science and Technology
Abstract
The reliable performance of artificial neural networks remains a central concern in the development of sugar mills throughout the region. The approach integrates adaptive control with experimental calibration to improve predictive accuracy. An increase of 39% in efficiency is shown to be possible through the modifications proposed here. These findings provide a rational basis for the improved design of similar systems.
Keywords:
artificial neural networksadaptive controlneural networkswater qualityphotovoltaic cell
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