Author(s)

Shunyi Zhao ¹, Xucheng Shen ¹, Yongzhe Wang ¹

Affiliation(s)

¹ School of Medical Information Engineering, Anhui University of Chinese Medicine, Hefei, 230012, China

Corresponding Author

Shunyi Zhao

ABSTRACT

With the increasing demand for renewable energy, this study focuses on the quality and yield of cotton straw pyrolysis products using cotton straw as an important biomass resource. Based on previous studies, this paper analyses the relationship between the mixing ratio of cotton straw pyrolysis combinations and the product yields, and finds that there is a nonlinear relationship between most of the product yields and the mixing ratios, so a polynomial nonlinear regression model is used for prediction. Due to the limited amount of data, the GM(1,1) grey prediction model was also introduced for comparison and evaluation in order to improve the accuracy of the model. The nonlinear regression model was established by Least Square Method, and then the GM(1,1) model was used to analyse the yield of products under different pyrolysis combinations. The results showed that the GM(1,1) model performed well in terms of prediction accuracy. Taking the DFA/CS combination as an example, the scatter plots of the raw data against the predicted values intuitively showed that the GM(1,1) model had a high degree of fitting, small prediction error and good prediction performance. This study is expected to provide a scientific basis for the efficient use of cotton straw pyrolysis products and the sustainable development of cotton straw.

KEYWORDS

Cotton straw pyrolysis, Nonlinear prediction model, GM (1,1)

CITE THIS PAPER

Shunyi Zhao, Xucheng Shen, Yongzhe Wang, Study on the yield of cotton straw pyrolysis products based on nonlinear prediction and grey predictive analysis. Modern Physical Chemistry Research (2024) Vol. 4: 34-40. DOI: http://dx.doi.org/10.23977/mpcr.2024.040105.

REFERENCES

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