Academic Journal of Environment & Earth Science, 2023, 5(3); doi: 10.25236/AJEE.2023.050304.
Gaopeng Xiang1, Kaijun Guo2, Yuhu Li3, Hongnan Jin3, Rumeng Lin4
1School of Science, Heilongjiang University of Science and Technology, Harbin, 150022, China
2School of Electrical and Control Engineering, Heilongjiang University of Science and Technology, Harbin, 150022, China
3School of Management, Heilongjiang University of Science and Technology, Harbin, 150022, China
4School of Computer and Information Engineering, Heilongjiang University of Science and Technology, Harbin, 150022, China
In order to study whether the global temperature warms and the biggest factors affecting temperature change, this paper collects the global average temperature from 1900 to 2022, sets up an experimental group and a control group to train three types of grey prediction models to select the optimal model, selects the metabolic type and analyzes the error, and uses the least squares method to fill in the difference to achieve future temperature prediction, and judges whether the future temperature warms by comparing the century temperature growth rate. Then, the least squares method, multiple linear regression and comprehensive evaluation were used to analyze the influence between natural and regional factors and temperature change, and the influence factors of natural and human factors on temperature change were calculated by grey correlation to determine the maximum influencing factors. The results show that the temperature growth rate in the 20th century is 1.0412, and the temperature growth rate in the 21st century is 1.0958 higher than that of 0.0546 in the 20th century, so the global temperature will warm in the future; the biggest factor affecting global warming is "forest area", with an impact coefficient of 0.9376.
temperature change, grey prediction, least squares, grey correlation, comprehensive evaluation system
Gaopeng Xiang, Kaijun Guo, Yuhu Li, Hongnan Jin, Rumeng Lin. Research on whether global temperature warms and its influencing factors based on grey predictions. Academic Journal of Environment & Earth Science (2023) Vol. 5 Issue 3: 21-29. https://doi.org/10.25236/AJEE.2023.050304.
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