Assessment of the Content of Dry Matter and Dry Organic Matter in Compost with Neural Modelling Methods

Neural image analysis is commonly used to solve scientific problems of biosystems and mechanical engineering. The method has been applied, for example, assess the quality foodstuffs such as fruit vegetables, cereal grains, meat. can also be analyse composting processes. problem lets us formulate research hypothesis: it possible identify representative traits composted material that are necessary create a neural model supporting process assessment content dry matter organic in material. effect identification selected features methods resulted new original enabling effective matter. analysed by means parameters specifying colour compost. best developed models compost are: visible light RBF 19:19-2-1:1 (test error 0.0922) MLP 14:14-14-11-1:1 0.1722), mixed 30:30-8-1:1 0.0764) 7:7-9-7-1:1 0.1795). generated images taken had better qualitative characteristics.