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Advanced Optimization of Heavy Clay Products Quality by Using Artificial Neural Network Mode
(Belgrade : Serbian Ceramic Society, 2014)
The effects of firing temperature (800–1100°C), chemical composition (expressed in terms of
the content of major oxides - SiO2, Al2O3, Fe2O3, CaO, MgO, Na2O, K2O, MnO and
TiO2), as well as several shape formats of ...
Prediction and Optimization of Heavy Clay Products Quality
(Wiley Blackwell, 2014)
The effects of chemical composition, firing temperature (800-1100 °C), and several shape formats of laboratory brick samples on the final product quality were investigated. Prediction of the final laboratory products ...