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Updated: Feb 20, 2026

Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills
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Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills

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長期予測における多変数モデリングの再考:電力分解とポストカリブレーションによる効率的な単変数フレームワーク.

Hongchi Chen1, Jifei Tang1, Lanhua Xia1

  • 1organization=School of communication engineering, Hangzhou Dianzi University, city=Hangzhou, state=Zhejiang, postcode=310018, country=China.

Neural networks : the official journal of the International Neural Network Society
|February 18, 2026
PubMed
まとめ

この研究は,長期タイムシリーズ予測 (LTSF) の単変数モデルであるPDCNetを紹介しています. データの課題を効果的に処理し,複雑なモデルを上回り,メモリ使用量を削減します.

キーワード:
長期タイムシリーズの予測P3D分解による分解カリブレーション後のポスト.単変数モデリング

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