Abstract
Neural image analysis is commonly used to solve scientific problems of biosystems and mechanical engineering. The method has been applied, for example, to assess the quality of foodstuffs such as fruit and vegetables, cereal grains, and meat. The method can also be used to analyse composting processes. The scientific problem lets us formulate the research hypothesis: it is possible to identify representative traits of the image of composted material that are necessary to create a neural model supporting the process of assessment of the content of dry matter and dry organic matter in composted material. The effect of the research is the identification of selected features of the composted material and the methods of neural image analysis resulted in a new original method enabling effective assessment of the content of dry matter and dry organic matter. The content of dry matter and dry organic matter can be analysed by means of parameters specifying the colour of compost. The best developed neural models for the assessment of the content of dry matter and dry organic matter in compost are: in visible light RBF 19:19-2-1:1 (test error 0.0922) and MLP 14:14-14-11-1:1 (test error 0.1722), in mixed light RBF 30:30-8-1:1 (test error 0.0764) and MLP 7:7-9-7-1:1 (test error 0.1795). The neural models generated for the compost images taken in mixed light had better qualitative characteristics.
Highlights
The handling of sewage sludge generated during the treatment of domestic wastewater in urbanised areas is an important problem of waste management nowadays
The analysis showed that the MLP network was the optimal topology for the neural model used for the assessment of the dry organic matter content in compost
The images were obtained in three different lighting variants, i.e., visible light (VIS), ultraviolet light in the range of 315–400 nm (UVA), and mixed light (MIX) that was a combination of both sources
Summary
The handling of sewage sludge generated during the treatment of domestic wastewater in urbanised areas is an important problem of waste management nowadays. The amount of sewage sludge increases proportionally to the number and efficiency of sewage treatment plants [1]. It is estimated that by 2020 the amount of sewage sludge generated in the European Union exceeded 13 million tonnes annually [2]. Sewage sludge handling and disposal in highly developed and industrialised countries is both an economic and logistic problem, and above all, it is an environmental problem [3]. Combustion, anaerobic digestion, and composting are the most common sewage sludge handling methods [4,5]. The sewage sludge combustion process is characterised by a favourable energy balance
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