
Therefore, there is a need to develop a predictive model for the pyrolysis process under varying biomass properties for commercial applications.ĭr. This variability poses significant challenges to producing consistent and predictable quality bio-oil for utilization into biofuels at a commercial scale. In addition, the pyrolysis operating conditions such as pyrolysis temperature, heating rate, and residence time further influence product yields. The yield of bio-oil depends on the biomass feedstock composition which can vary widely depending upon the type of biomass, time of harvesting, and other logistical practices. Its thermochemical conversion technology converts lignocellulosic biomass into bio-oil, biochar and non-condensable gas mixtures. Sudhagar Mani.Ĭomplex processes such as pyrolysis, a promising technology for converting biomass into renewable biofuels, can benefit greatly from machine learning. The biomass industry is no exception, and TAPPI’s International Bioenergy and Bioproducts Conference (IBBC), October 30 – November 2, Providence, RI, surfaces potential approaches, including a presentation by the University of Georgia’s Dr. And more precise models can help organizations across all industries identify new opportunities and avoid risks. These elements make it possible to produce models that can analyze bigger, more complex data and deliver faster, more accurate results.

Today there has been a resurging interest in ML due to key factors such as large volumes and varieties of available data, faster and more powerful computational processing, affordable data storage, and more reliable algorithms. ML models can identify patterns from a dataset and automatically learn without being programmed.
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A subset of AI, Machine Learning (ML) trains a machine how to learn. Perhaps with better algorithms and accurate data, Hal would have been as docile as Alexa and Siri.Īrtificial Intelligence (AI) is the science of training machines to perform human tasks. Effective and reliable AI requires accurate data and timely processing.

But many of the problems and challenges of Artificial Intelligence (AI) introduced in the film still face us today.
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