MACHINE LEARNING POWERED SOFTWARE FOR ACCURATE PREDICTION OF BIOGAS PRODUCTION: A CASE STUDY ON INDUSRTIAL

TÍTULO

MACHINE LEARNING POWERED SOFTWARE FOR ACCURATE PREDICTION OF BIOGAS PRODUCTION: A CASE STUDY ON INDUSRTIAL - SCALE CHINESE PRODUCTION DATA

DOCUMENTO - ARTIGO CIENTÍFICO 

AUTORES - DJAVAN DE CLERCQ, DEVANSH JALOTA, RUOXI SHANG, KUNYI NI, ZHUXIN ZHANG, AREEB KHAN, ZONGGUO WEN, LUIZ CAICEDO, KAI YUAN

RESUMO/ABSTRACT

The search for appropriate models for predictive analytics is currently a high priority to optimize anaerobic fermentation processes in industrial-scale biogas facilities; operational productivity could be enhanced if project operators used the latest tools in machine learning to inform decision-making. The objective of this study is to enhance biogas production in industrial facilities by designing a graphical user interface to machine learning models capable of predicting biogas output given a set of waste inputs. The methodology involved applying predictive algorithms to daily production data from two major Chinese biogas facilities in order to understand the most important inputs affecting biogas production. The machine learning models used included logistic regression, support vector machine, random forest, extreme gradient boosting, and k-nearest neighbors regression. The models were tuned and crossvalidated for optimal accuracy. Our results showed that: (1) the KNN model had the highest model accuracy for the Hainan biogas facility, with an 87% accuracy on the test set; (2) municipal fecal residue, kitchen food waste, percolate, and chicken litter were inputs that maximized biogas production; (3) an online web-tool based on the machine learning models was developed to enhance the analytical capabilities of biogas project operators; (4) an online waste resource mapping tool was also developed for macro-level project location planning. This research has wide implications for biogas project operators seeking to enhance facility performance by incorporating machine learning into the analytical pipeline.

Profissionais, estudantes e interessados na cadeia do biogás e, atuantes nas diversas áreas, etapas de projetos ou operação na produção de biogás.