PET Viscosity Prediction Using JIT-based Extreme Learning Machine
PET Viscosity Prediction Using JIT-based Extreme Learning Machine is a scholarly work, published in 2018 in ''IFAC Proceedings Volumes''. The main subjects of the publication include biological system, viscometer, artificial intelligence, lithium-ion battery, process engineering, proton exchange membrane fuel cell, work, process, extreme learning machine, viscosity, materials science, and computer science. The industrial PET viscosity prediction results show the improved prediction performance of the proposed modeling approach in comparison with ELM and JPCR (Just-in-time principal component regression) approaches.