地球科学における数値モデルの検証,検証,確認
まとめ
自然システムの数値モデルは,その固有の複雑性と非ユニークな結果のために,完全に検証または検証することはできません. 予測と観測を一致させることでモデルが確認できるが,この確認は常に部分的であり,そのヒューリスティック価値を強調する.
科学分野:
- 環境モデリング
- 計算科学とは,計算科学である.
- 科学の哲学 科学の哲学
背景:
- 数値モデルは,自然のシステムをシミュレートするために広く使用されています.
- これらのモデルの厳格な検証と検証は,それらの信頼性の高い適用のために不可欠です.
- 複雑でオープンなシステムを表現するモデルの絶対的精度を確立するにあたって,課題が存在します.
研究 の 目的:
- 自然システムの数値モデルに適用される検証と検証の概念を批判的に評価する.
- 科学的実践におけるモデル確認の限界と影響を調査する.
- 科学モデルの主要な有用性を再定義する.
主な方法:
- 検証,検証,確認の概念の論理的分析.
- 科学的モデリングの哲学的基盤の検討,インダクションの問題と結果の肯定を含む.
- 自然システムの固有特性 (例えば,開放性) とモデルアウトプット (例えば,非ユニーク性) の議論.
主要な成果:
- 自然システムモデルの完全な検証と検証は,論理的に不可能です.
- 自然のシステムはオープンで,モデル結果はしばしば非ユニークで,絶対的な確実性を排除します.
- 予測と観察の間の合意に基づくモデルの確認は,部分的で,論理的誤謬の対象となります.
- モデルの予測価値は,本質的に不確実なままです.
結論:
- 自然システムのモデルは,相対的にしか評価できないし,絶対的な検証はできない.
- 数値モデルの主な価値は,決定的な真実ではなく,理解と調査を支援するヒューリスティックな機能にあります.
- 科学的実践は,モデル確実性の固有の限界を認識し,知識の進歩におけるその役割に焦点を当てなければならない.
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