DKWM-XLSTM:考虑多种影响因素的碳交易价格预测模型
Yunlong Yu1, Xuan Song1, Guoxiong Zhou1
1School of Economics & Management, Central South University of Forestry and Technology, Changsha 410004, China.
Entropy (Basel, Switzerland)
|August 28, 2025
概括
这项研究引入了一种用于预测碳交易价格波动的新方法,提高了气候变化缓解努力的准确性. 这种方法提高了碳金融衍生品的定价和交易系统中的风险管理.
科学领域:
- 环境科学
- 减缓气候变化
- 金融市场
背景情况:
- 森林碳汇对于减缓气候变化和碳交易系统至关重要.
- 遥感对于监测碳汇和预测碳价格至关重要.
- 由于碳价格的不稳定性和不确定性, 预测碳价格具有挑战性.
研究的目的:
- 开发一种可靠的方法来预测多因素影响的碳交易价格.
- 解决非静态数据的复杂性和碳市场内在的不确定性.
- 提高碳价格预测的准确性和可靠性.
主要方法:
- 一个分解 (DECOMP) 模块将数据分成趋势和周期组件.
- 具有多域扩散 (KAN-MD) 模块的KAN提取特征并管理非静止性.
- 使用波形变换的波MH注意模块可以减少不确定性干扰.
主要成果:
- 拟议的模型在湖北碳交易市场上显示出卓越的预测准确性.
- 达到0.204%的平均平方误差 (MSE) 和0.0277的平均绝对误差 (MAE).
- 与基准方法相比,该模型对价格波动具有更强的弹性.
结论:
- 开发的方法提供了可靠的碳价格预测方法.
- 结果支持改善碳金融衍生品的定价.
- 这项研究有助于改善碳交易市场的风险管理.
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