首页|Silesian University of Technology Reports Findings in Machine Learning [Application of a generalized hybrid machine learning model for the prediction of H2S and VOCs removal in a compact trickle bed bioreactor (CTBB)]
Silesian University of Technology Reports Findings in Machine Learning [Application of a generalized hybrid machine learning model for the prediction of H2S and VOCs removal in a compact trickle bed bioreactor (CTBB)]
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News - New research on Machine Learning is th e subject of a report. According to news reporting from Gliwice, Poland, by News Rx journalists, research stated, “This study presents a generalized hybrid model for predicting HS and VOCs removal efficiency using a machine learning model: K - NN (K - nearest neighbors) and RF (random forest). The approach adopted in th is study enabled the (i) identification of odor removal efficiency (K) using a c lassification model, and (ii) prediction of K<100% , based on inlet concentration, time of day, pH and detention time.”
GliwicePolandEuropeCyborgsEmergi ng TechnologiesMachine Learning