適応エントロピー加重グレー関係とデンプスター・シャファー理論を統合した非線形システムの状態信頼性分析方法
Liming Gou1,2, Jian Zhang1,3, Lin Qi1,4
1College of Management Science and Engineering, Beijing Information Science & Technology University, Beijing, China.
PloS one
|February 13, 2026
まとめ
この研究では,不確実性下でシステムの故障を予測するための新しいモデルを導入し,精度を4.5%改善しました. 強化された分析法により,システムの信頼性確率評価の精度は5.22%増加しました.
科学分野:
- エンジニアリング エンジニアリング
- システム分析 システム分析
- 信頼性のエンジニアリング
背景:
- 不確実な環境条件により,非線形システムは情報衝突,曖昧さ,損失を経験し,正確な異常状態の予測を妨げます.
- 不確実な状況下でのシステムの故障は,重大な悪影響を及ぼし,予測と評価の方法論の改善を必要とする.
研究 の 目的:
- 不確実な条件下で動作する非線形システムの高度な分析モデルを開発する.
- 異常なシステム状態を予測し,システムの信頼性を評価する精度を高めるため.
主な方法:
- 分析モデルに因子重量の適応調整を組み込むこと.
- 不確実性と相関因子の評価と定量化のためのデンプスター・シャファー理論 (D-S理論) アルゴリズムの統合.
主要な成果:
- 提案されたモデルは,風力タービンのケーススタディで97%のシステム状態識別精度を達成しました.
- システムの信頼性の確率は65%と評価され,従来の方法よりも5.22%の改善を示した.
- 既存のアルゴリズムと比較して,全体の精度4.5%の改善が観察されました.
結論:
- 開発されたモデルは,情報の不確実性の分析の正確性への影響を効果的に軽減します.
- このアプローチは,システムの信頼性確率評価の精度を高め,意思決定を改善します.
- アルゴリズムは,実際のシステム状態の確率分布と整合する上で優れたパフォーマンスを示しています.
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