Artificial neural network for optimization of a synthesis process of γ -bi 2 moo 6 using surface response methodology

摘要: In this work an artificial neural network was utilized in order to optimize the synthesis process of γ-Bi2MoO6 oxide by co-precipitation assisted with ultrasonic radiation. This is recognized as efficient photocatalyst for degradation organic pollutants aqueous media. For three variables were considered, exposure time radiation, calcination and temperature. The efficiency photocatalysts synthesized evaluated photodegradation rhodamine B (rhB) under sun-like irradiation. A set experimental data introduced into network, a multilayer type perceptron back-propagation learning rule used simulate results modifying one input observing using besides response surface methodology.