在地球科学中的数值模型的验证,验证和确认
概括
自然系统的数值模型不能完全验证或验证,因为它们的内在复杂性和非独特的结果. 虽然模型可以通过将预测与观测相匹配来确认,但这种确认总是局部的,突出了它们的启发性价值.
科学领域:
- 环境建模环境建模
- 计算科学是一种计算科学.
- 科学哲学的科学哲学.
背景情况:
- 数字模型被广泛用于模拟自然系统.
- 这些模型的严格验证和验证对于它们的可靠应用至关重要.
- 在建立代表复杂,开放系统的模型的绝对准确性方面存在挑战.
研究的目的:
- 批判性地评估验证和验证的概念,应用于自然系统的数值模型.
- 探索模型确认在科学实践中的局限性和影响.
- 重新定义科学模型的主要实用性.
主要方法:
- 对验证,验证和确认的概念进行逻辑分析.
- 检查科学建模的哲学基础,包括诱导问题和肯定后果.
- 讨论自然系统的固有特征 (例如,开放性) 和模型输出 (例如,非独特性).
主要成果:
- 自然系统模型的完整验证和验证在逻辑上是不可能的.
- 自然系统是开放的,模型结果往往不是唯一的,排除了绝对的确定性.
- 基于预测和观察之间的协议的模型确认是局部的,并且可能存在逻辑谬误.
- 模型的预测价值仍然存在固有的不确定性.
结论:
- 自然系统的模型只能在相对方面进行评估,不能得到绝对验证.
- 数字模型的主要价值在于它们的启发式功能 - - 帮助理解和探索,而不是确定真相.
- 科学实践必须承认模型确定性的固有局限性,并专注于它们在知识推进中的作用.
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