使用通用添加模型 (GAM) 测量负责任因素对CO2排放的影响
Ruhul Amin1, Md Sifat Ar Salan1, Md Moyazzem Hossain1
1Department of Statistics and Data Science, Jahangirnagar University, Savar, Dhaka, 1342, Bangladesh.
Heliyon
|February 20, 2024
概括
这项研究表明,通用添加模型 (GAM) 是预测孟加拉国二氧化碳 (CO2) 排放的最佳方法. GAM准确地预测二氧化碳排放,帮助可持续发展战略.
科学领域:
- 环境科学 环境科学
- 计量经济学 计量经济学
- 可持续发展 可持续发展 可持续发展
背景情况:
- 经济和可持续发展指标受到二氧化碳 (CO2) 排放的重大影响.
- 孟加拉国因人口增长,工业化和电力需求增加而面临二氧化碳排放量的增加.
- 了解二氧化碳排放趋势对于环境和经济政策至关重要.
研究的目的:
- 探索孟加拉国二氧化碳排放与相关指标之间的关系.
- 确定预测二氧化碳排放的最有效模型.
- 评估不同统计模型的预测准确度.
主要方法:
- 从世界银行和孟加拉国道路运输管理局收集了1971-2020年的二次数据.
- 在二氧化碳排放建模中使用了通用增量模型 (GAM),多项式回归 (PR) 和多重线性回归 (MLR).
- 使用RMSE,MSE,AIC,BIC和R平方指标评估模型性能.
主要成果:
- 确定了多对线性问题以及二氧化碳排放和相关因素之间的非线性关系.
- 在GAM模型中,RMSE,MSE,AIC,BIC的最低值和R平方值的最高值 (0.996) 显示出卓越的性能.
- 与MLR和PR相比,GAM被证明是预测孟加拉国二氧化碳排放的最准确模型.
结论:
- 一般化添加模型 (GAM) 是预测孟加拉国二氧化碳排放的有效工具.
- 研究结果强调了二氧化碳排放和相关风险因素的非线性性质.
- 结果可以为决策者制定低碳经济,可再生能源和可持续环境技术进步的战略提供信息.
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