Analysis of bioenergy by using linear regression

被引:3
作者
Iqbal, Muhammad Shahid [1 ,2 ]
Khan, Tamoor [3 ]
Kausar, Samina [4 ]
Bin, Luo [1 ]
机构
[1] Anhui Univ, Sch Comp Sci & Technol, Hefei, Anhui, Peoples R China
[2] Air Univ, Dept Comp Sci, Islamabad, Pakistan
[3] Southwestern Univ Finance & Econ, Sch Econ Informat Engn, Chengdu, Sichuan, Peoples R China
[4] Shanghai Univ, Sch Comp Engn & Sci, Shanghai 200444, Peoples R China
来源
SN APPLIED SCIENCES | 2019年 / 1卷 / 10期
关键词
Bioenergy; Energy production; Linear regression model; Yearly production; International renewable energy agency; BIO-ENERGY; DEVELOPING-COUNTRIES; BIOMASS;
D O I
10.1007/s42452-019-1270-1
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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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页数:11
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