Complex Systems in Earth Sciences: Predictability, Mitigation and Reduction of Natural Hazards

地球科学中的复杂系统：自然灾害的可预测性、缓解和减少

• 批准号: 9318648
• 负责人: John Rundle
• 金额: $ 1.13万
• 依托单位: Santa Fe Institute
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1994
• 资助国家: 美国
• 起止时间: 1994-01-01 至 1995-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9318648&HistoricalAwards=false
• 关键词: Complex; Systems; Earth; Sciences; Predictability

9318646 Rundle It has been recognized by the international community that it may be possible, through programs of systematic study, to devise means to reduce and mitigate the occurrence of a variety of devastating natural hazards (see appendix). One of the most promising avenues of approach is to develop the capability to simulate these physical processes in the computer. Many of the recent models are nonlinear in significant ways, including cellular automata-type or fractal growth models, and can thus be analyzed in a framework familiar to workers in complex system theory. Moreover, it is often the case that the occurrence frequency of disaster events generated by the models follow power laws. While recognizing the importance of this new approach, at this time earth scientists do not generally possess the skills needed to develop or analyze these models. Moreover, it is clear that a variety of workers in statistical mechanics, applied mathematics, and other fields have developed significant interest in these nontraditional problems. The development and analysis of simulations for these problems would therefore proceed most expeditiously in an interdisciplinary professional setting such as that provided by the Santa Fe Institute. A workshop be held at SFI to address these issues, and to allow a forum in which earth scientists can interact with physicists and mathematicians developing techniques to simulate and analyze complex systems.

小行星9318646 国际社会已经认识到，通过系统研究方案，有可能制定减少和减轻各种破坏性自然灾害发生的手段（见附录）。 最有前途的途径之一是开发在计算机中模拟这些物理过程的能力。 许多最近的模型是非线性的显着方式，包括元胞自动机型或分形增长模型，因此可以在复杂系统理论的工作人员熟悉的框架进行分析。 此外，由模型生成的灾害事件的发生频率往往遵循幂律。 虽然认识到这种新方法的重要性，但目前地球科学家通常不具备开发或分析这些模型所需的技能。 此外，很明显，统计力学、应用数学和其他领域的各种工作者对这些非传统问题产生了浓厚的兴趣。 因此，在圣菲研究所提供的跨学科专业环境中，将最迅速地进行这些问题的模拟开发和分析。 在SFI举办一个研讨会来解决这些问题，并允许一个论坛，地球科学家可以与物理学家和数学家互动，开发模拟和分析复杂系统的技术。