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• W3084966153 abstract "In this work, the algal biomass productivity and its lipid content were explored using a database containing 4670 instances extracted from the experimental results reported in 102 published articles. First, the influences of critical factors such as microalgae species, cultivation conditions, light intensity, CO 2 amount, nutrient concentrations, reactor type, stress conditions, cell disruption methods, and lipid extraction solvents on the biomass and lipid production were reviewed. Then, the database was analyzed using machine learning techniques; decision trees were utilized to determine the combination of variables leading to high biomass and lipid content while association rule mining was used to find the specific conditions leading to very high biomass and lipid levels. Decision tree analysis discovered 11 different combinations of variables leading to high biomass productivity and 13 combinations for high lipid content; whereas, association rule mining analysis helped to identify the levels of specific factors for very high biomass and lipid production. It was then concluded that machine learning methods can help to determine the best conditions for optimum biomass growth and lipid yield for microalgae to manufacture renewable biofuels, and this can guide the planning of new experimental works. • machine learning provided the optimum conditions of biomass growth and lipid yield. • Decision trees discovered 11 combination of variables for high biomass productivity. • CO 2 content, photoperiod, feed low and light intensity affect biomass significantly. • N and PO 4 , pH and salinity level of the medium influence lipid yield excessively. • machine learning on algal database can be a guide for industrial scale up." @default.
• W3084966153 created "2020-09-21" @default.
• W3084966153 creator A5026887831 @default.
• W3084966153 creator A5057251374 @default.
• W3084966153 creator A5083517243 @default.
• W3084966153 date "2021-01-01" @default.
• W3084966153 modified "2023-10-12" @default.
• W3084966153 title "Exploring the critical factors of algal biomass and lipid production for renewable fuel production by machine learning" @default.
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