Journal
SN APPLIED SCIENCES
Volume 1, Issue 10, Pages -Publisher
SPRINGER INTERNATIONAL PUBLISHING AG
DOI: 10.1007/s42452-019-1270-1
Keywords
Bioenergy; Energy production; Linear regression model; Yearly production; International renewable energy agency
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Funding
- School of Computer Sciences, Anhui University Hefei, China
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Prediction of bioenergy production is challenging in the machine learning field. In this article, bioenergy production data from different countries (Russian Fed, Turkey, Armenia, Azerbaijan and total Eurasia) were analyzed to predict future bioenergy production in these countries using the linear regression. Data on output production of bioenergy in megawatt were obtained from the International Renewable Energy Agency, and (MW). We implemented the linear regression method redundant to predict the future production of bioenergy data and attained good accuracy. The aforementioned method is applicable to developing countries and can be used to predict bioenergy production and formulate new policies that are adapted to an increasing population in a particular country. Our results (average accuracy is 49.61%) revealed that bioenergy production levels in developing countries are not sufficient to cater for bioenergy needs of fast growing populations. Thus we recommend that governments should formulate adequate policies aimed at improving bioenergy production.
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