AI RESEARCH
A Comparative Analysis of Machine Learning Algorithms for Multi-Task Prediction of the Parameters of the Pectin Hydrolysis--Extraction Process
arXiv CS.LG
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ArXi:2606.00821v1 Announce Type: new This study addresses the challenge of controlling a complex, multi-parameter technological process -- pectin hydrolysis--extraction -- using machine learning methods. The experimental foundation is a unique database comprising 1,000 laboratory experiments conducted under controlled conditions on seven types of plant raw material with four variable process factors (temperature 85--130 C, pressure 0.9--2.2 atm, holding time 3--10 min, pH 1.5--2.0