一个新的分数级灰色预测模型:对中国碳排放的案例研究
Hui Li1, Zixuan Wu2, Shuqu Qian1
1School of Mathematics and Computer Science, Anshun University, Anshun, Guizhou, 561000, China.
Environmental science and pollution research international
|October 2, 2023
概括
一个新的分数级灰色模型准确地预测了中国的碳排放量,比传统方法更好. 这种方法有助于设定减排目标,并为气候政策决策提供信息.
科学领域:
- 环境科学 环境科学
- 数学建模的数学建模
- 气候变化分析 气候变化分析
背景情况:
- 准确的碳排放预测对于国家减排目标和政策实施至关重要.
- 预测碳排放峰值为战略规划提供了宝贵的见解.
- 现有的模型可能无法完全捕捉到排放动态的复杂性.
研究的目的:
- 为中国的碳排放开发一种新的分数级灰色多变量预测模型.
- 通过结合分数顺序的累积序列来提高预测准确度.
- 为了验证模型的有效性与已建立的灰色预测方法.
主要方法:
- 建立了一个包含马函数的分数级灰色多变量预测模型.
- 使用粒子群算法来优化累积序列顺序.
- 将模型应用于21年的中国碳排放数据以进行验证.
主要成果:
- 拟议的粒子群优化分数顺序模型与灰色多变量和经典灰色预测模型相比,显示出更高的性能.
- 该模型表现出稳定的模拟和预测特征,准确度高.
- 在三个案例中的验证证实了该模型的有效性.
结论:
- 新型分数级灰色模型为预测碳排放提供了强大而准确的工具.
- 该模型的准确性和稳定性为中国的减排战略提供了宝贵的支持.
- 未来的研究可以将这种模型应用于其他环境预测挑战.
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