Neural Network Modeling to Support an Experimental Study of the Composting Process of Biowaste With Filter Cake and Star Grass

Abstract

Biowaste (B) is the predominant fraction of municipal solid waste (MSW) in developing countries and composting is one of the most widely used technologies for the use of biowaste. Several interrelated factors affect the efficiency of the bioconversion of the substrate influencing the development of the composting process and therefore, the quality of the final product. Simulations through Artificial Neural Networks-ANN allows to determine the influence of these factors and to make predictions that improve the process and the quality of the final product which providing the definition of real criteria for the implementation of the technology. This study shows the feasibility of simulating, with feedforward ANN, the composting process at a pilot scale by mixing with biowaste, Filter cake (FC) and star grass (SG). Experiments were carried out with a Box-Bemkhen design, simultaneously evaluating factors such as the mixing ratio (MR) of B: