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Modeling and Similitude01:12

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Scaled modeling is a fundamental technique in engineering, enabling the study of large and complex systems by creating smaller, manageable replicas that recreate critical characteristics of the original. In hydrology and civil infrastructure, for example, scaled models of dams help analyze water flow, turbulence, and pressure. This method allows for accurate predictions of real-world behavior within a controlled environment, significantly reducing the cost and time involved in full-scale...
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Fluid mechanics model studies often utilize scaled-down systems to predict fluid behavior in full-scale environments, such as river flows, dam spillways, and structures interacting with open surfaces. Maintaining Froude number similarity in river models is crucial, as it replicates surface flow features like wave patterns and velocities.
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Drug clearance is a critical pharmacokinetic process involving the irreversible removal of drugs from the body through various organs over a specified time period. Physiological models are indispensable in determining organ-specific clearance, defined by the proportion of the drug eliminated per unit of time from the organ's blood volume.
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Scientists frequently use models to help them comprehend a specific collection of phenomena. In physics, a model is a condensed version of a physical system that is too complex to study thoroughly. One such example is the light wave model; unlike water waves, light waves are typically invisible to us. Nonetheless, it is helpful to think of light as being composed of waves, since investigations show that light behaves like water waves. Since it is impossible to visually see what is genuinely...
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Language serves as a bridge between ideas and communication, influencing how individuals perceive and interact with the world. Psychologists have long debated whether language shapes thought or vice versa. This discussion gained grip with Edward Sapir and Benjamin Lee Whorf in the 1940s, who proposed that language determines thought, a concept known as linguistic determinism. They suggested that the vocabulary and structure of a language influence how its speakers think and perceive reality.
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相关实验视频

Updated: Jan 7, 2026

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
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环境建模的大型语言模型:框架,能力,约束

Qiyang Nie1, Tong Liu2

  • 1Graduate School of Environmental Science, Hokkaido University, Sapporo, 060-0810, Japan.

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概括

大型语言模型 (LLM) 为环境建模提供了新的途径. 人与人工智能的Copilot框架在参数校准和实时校正方面表现出色,而Autopilot则面临局限性.

关键词:
自动驾驶系统框架校准 校准 校准 校准 校准 校准共同飞行员框架 共同飞行员框架环境建模环境建模洪水模型的洪水模型.大型语言模型.实时校正 实时校正

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科学领域:

  • 环境科学 环境科学
  • 人工智能的人工智能
  • 计算建模 计算建模

背景情况:

  • 环境建模的复杂性正在增加.
  • 将大型语言模型 (LLM) 集成到这些工作流中存在挑战.
  • 需要在环境建模中整合LLM的实际框架.

研究的目的:

  • 引入和评估将LLM嵌入环境建模工作流程的两个框架:一个人-AI协作Copilot和一个LLM驱动的Autopilot.
  • 通过RRI模型评估这些框架在参数校准和实时校正方面的性能.
  • 为环境建模中LLM的普遍化部署提供指导.

主要方法:

  • 开发两种LLM集成框架:Copilot (人类-AI协作) 和Autopilot (LLM驱动的自动化).
  • 将框架应用于日本库祖鲁河流域的降雨-排水-洪水 (RRI) 模型.
  • 评估参数校准和实时校正任务的性能,利用快速工程和物理约束.

主要成果:

  • 柯皮洛特框架表现出强大的性能,实现了参数校准的高精度 (NSE 0.91/0.81) 和稳定的实时校正.
  • 自动驾驶框架在受物理约束的校准中表现出能力,但由于"注意力衰减",在长序实时校正中失败了.
  • 在人类监督下,LLM作为知识引擎和编码助手是有效的 (Copilot),但完全自动化 (Autopilot) 受到上下文窗口限制的限制.

结论:

  • 人与人工智能的协作框架 (Copilot) 目前在复杂的环境建模任务中比完全自动化的框架 (Autopilot) 更有效.
  • 战略任务设计,人类监督,以及解决LLM诸如"注意力衰减"等局限性,对于成功的LLM整合至关重要.
  • 该研究提供了一个方法框架和设计原则,用于在环境建模中部署LLMs,突出未来的研究方向.