Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Researchers detail new data in Machine Learning. According to news reporting originating from Anhui, People’s Republic of China, by NewsRx correspondents, research stated, “In this work, the yields of bio-BTX (biomass-derived benzene, toluene and xylene) and light olefins from zeolitecatalyzed biomass pyrolysis were predicted for the first time via machine learning methods based on various experimental parameters, including biomass ch aracteristics, catalyst properties and pyrolysis conditions. Random forest (RF), gradient boosting decision tree and extreme gradient boosting algorithms were u sed for evaluation, and the results reveal that the RF algorithm has the highest prediction accuracy with the high test R2 values (0.91-0.97) for all models.”
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