Determination of dry matter content in composted material based on digital images of compost taken under mixed visible and UV-A light

摘要

The aim of the research was to investigate the possibility of using the methods of neural image analysis and neural modeling to determine the content of dry weight of compost based on photographs taken under mixed visible and UV-A light conditions. The research lead to the conclusion that the neural image analysis may be a useful tool in determining the quantity of dry matter in the compost. Generated neural model RBF 30:30-8-1:1 characterized by RMS error 0,076378 and this networks is more effective than RBF 19:19-2:1:1 which works in visible light conditions.