Machine learning prediction of bio-oil production from the pyrolysis of lignocellulosic biomass: Recent advances and future perspectives
Journal of Analytical and Applied Pyrolysis, ISSN: 0165-2370, Vol: 179, Page: 106486
2024
- 6Citations
- 28Captures
- 1Mentions
Metric Options: CountsSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Most Recent News
Studies from Korea Institute of Energy Research Add New Findings in the Area of Machine Learning (Machine Learning Prediction of Bio-oil Production From the Pyrolysis of Lignocellulosic Biomass: Recent Advances and Future Perspectives)
2024 JUN 11 (NewsRx) -- By a News Reporter-Staff News Editor at Energy Daily News -- Investigators publish new report on Machine Learning. According to
Review Description
Bio-oil produced through pyrolysis of lignocellulosic biomass has recently received significant attention due to its possible uses as a second-generation biofuel. The yield and characteristics of produced bio-oil are affected by reaction conditions and the type of feedstock that is used. Recently, machine learning (ML) techniques have been widely employed to forecast the performance of the pyrolysis and the characteristics of bi-oil. In this study, a comprehensive review of ML research on bio-oil has been carried out. Regression methods were most frequently employed to build prediction models and the top five ML methods for bio-oil research were random forest, artificial neural network, gradient boosting, support vector regression, and linear regression. The prediction results through the developed models were quite consistent with experiment results. However, studies to data have had limitations such as the used of restricted data, extraction features using their own knowledge, and limited used of ML algorithms. We highlighted the challenges and potential of cutting-edge ML techniques in bio-oil production.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S0165237024001414; http://dx.doi.org/10.1016/j.jaap.2024.106486; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85189545227&origin=inward; https://linkinghub.elsevier.com/retrieve/pii/S0165237024001414; https://dx.doi.org/10.1016/j.jaap.2024.106486
Elsevier BV
Provide Feedback
Have ideas for a new metric? Would you like to see something else here?Let us know