Maturity classification for composted sewage sludge and rapeseed straw mixture based on neural analysis of images acquired in UV-A light

Abstract

Composting is one of the most efficient ways of managing municipal sewage sludge. Recently, due to the increased demand for composting, the issue of conducting this process in cost effective way is of particular importance. Determining the early maturity stage of the composted material can significantly improve the efficiency of surface management of relatively expensive compost plant. The following research presents classification of neural models for determining the early stage of composted mixture of sewage sludge and rapeseed straw, basing on information contained in images of material samples obtained with UV-A illumination. The topology of the MLP network was used in the construction of classification models. As input variables, 25 color parameters and 21 texture parameters were originally used, but also steps were taken to eliminate their number. The classification error for the developed neural models ranged from 1.83 to 4.27%. The best model in terms of the lowest value of error, and the smallest number of input variables required, included 16 neurons in the input layer, 50 neurons in the hidden layer and 2 neurons in the output layer. The following model is characterized by a slightly lower classification error and a slightly simpler structure than the best possible model developed in earlier studies for visible light illumination.

Authors and Affiliations

Sebastian Kujawa

Keywords

Related Articles

Changes in meadow communities on abandoned marshy meadows

The study was carried out in the years 2010-2013 on drained, unused meadows situated on organic soils (wet and humid) in central Poland. The paper presents the changes and transformations of habitats and meadow communiti...

Assessment of the accuracy of the approximate method used to estimate the heating power demand for single-family houses

Total design heat load as well as the approximate method based on the thermal characteristics of the building were deter-mined in accordance with the PN-EN 12831 standard for 84 randomly selected single-family residentia...

Wind power in Poland and Ukraine – condition today and prospects for tomorrow

The purpose of this study is to compare the condition and development prospects of the wind power sector in Poland and Ukraine. Our research is based on reports and studies prepared by industry organizations associating...

Влияние содержания Nмин на динамику накопления сухого вещества, а также показатели эффективности использования азота в ювенальной фазе кукурузы

B процессе полевых исследований изучалось влияние разных азотных удобрений, дозы азота и содержание минерального азота в почве перед посевом кукурузы на динамику первоначального роста, содержание, аккумуляцию азота, а та...

The influence of the crop farming system on the health of spring triticale in the mountain conditions of the Beskid Niski

The aim of the study was to compare the occurrence intensity of fungal diseases on leaves, ears and the stem base of spring triticale in pure and mixed sowing grown using the conventional and organic method in mountain c...

Download PDF file
  • EP ID EP514883
  • DOI -
  • Views 235
  • Downloads 0

How To Cite

Sebastian Kujawa (2018). Maturity classification for composted sewage sludge and rapeseed straw mixture based on neural analysis of images acquired in UV-A light. Journal of Research and Applications in Agricultural Engineering (ISSN 1642-686X), 63(4), 94-100. https://europub.co.uk/articles/-A-514883