Application of Multi Layered Perceptron Neural Network for Modeling Biodiesel Yield

Biodiesel preparation is broadly led through transesterification process, with homogeneous or heterogeneous catalyst. The most remarkable catalyst utilized in preparing biodiesel is the homogeneous catalyst, for example, NaOH, KOH, Na2O2 and CH3ONa. The decision of selecting among these catalysts is because of their higher response rates. Accordingly this paper examines the impacts of various catalyst utilized for preparing biodiesel using Mahua oil. Machine learning has demonstrated to be an amazing for various modeling during the previous decades. Multi Layered Perceptron based Artificial neural networks (ANN), stands out amongst the most prominent modeling methods investigated. The utilization of MLP for improvement of catalyst in bio diesel preparation was not well studied until ongoing decades. In this analysis, the focus is on the use of MLP based ANNs for catalysis advancement in biodiesel preparation. From the points of view of experimental analysis and ANN modeling, this investigation indicates how MLPs can be adequately connected for catalyst optimization in biodiesel preparation