DKWM-XLSTM:複数の影響要因を考慮した炭素取引価格予測モデル
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
まとめ
この研究は,変動する炭素取引価格を予測する新しい方法を導入し,気候変動緩和の取り組みの精度を向上させます. このアプローチは,取引システムにおける炭素金融デリバティブの価格設定とリスク管理を強化します.
科学分野:
- 環境科学
- 気候変動の緩和
- 金融市場
背景:
- 森林の炭素吸収は 気候変動の緩和と 炭素取引システムにとって不可欠です
- 炭素吸収を監視し,炭素価格を予測するために,遠隔感知は非常に重要です.
- 炭素価格の予測は不動性や不確実性のために困難です.
研究 の 目的:
- 複数の要因が影響する炭素取引価格を予測するための堅実な方法を開発する.
- 停滞しないデータの複雑さと炭素市場の固有の不確実性に対処する.
- 炭素価格の予測の正確性と信頼性を高めること
主な方法:
- 分解 (DECOMP) モジュールは,データを傾向と周期的な構成要素に分けます.
- 多領域拡散 (KAN-MD) モジュールは,特性を抽出し,非静止性を管理します.
- Wave-MH 注意モジュールは,ウェーブレット変換を使用して,不確実性の干渉を軽減します.
主要な成果:
- 提案されたモデルは,湖北の炭素取引市場における優れた予測精度を示しています.
- 平均二乗誤差 (MSE) は0. 204%で,平均絶対誤差 (MAE) は0. 0277でした.
- このモデルは,ベンチマーク方法と比較して,価格変動に対する回復力を高めています.
結論:
- 開発された方法は,炭素価格の予測のための信頼性の高いアプローチを提供します.
- 結果は炭素金融デリバティブの価格の改善を支持している.
- この研究は,炭素取引市場におけるリスク管理の改善に寄与する.
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