SGER: Frame-based Ecosystem Modeling
SGER: Frame-based Ecosystem Modeling
批准号:
9314432
负责人:
Anthony Starfield
金额:
$5.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
1993
资助国家:
美国
项目状态:
已结题
起止时间:
1993-09-15 至 1996-02-29
中文摘要
9314432斯塔菲尔德这个研究项目将开发一种模拟生态系统动态的范例。该范式使用借用自人工智能的框架语法,分别对系统的不同状态进行建模。在每一帧中,简单的模型(无论是数值的还是定性的)模拟相应生态状态的关键过程。“恶魔”观察国家定义背后的假设是否被违反,如果是的话,在不同的框架中切换到不同的模型。这种方法极大地方便了建立动态生态系统模型的过程。它使快速检验假设成为可能,并导致易于理解的模型,从而促进思想的交流。它还适用于包括正在进行的过程(如竞争和食草动物)和零星事件(如火灾)之间相互作用的模型,其分辨率水平足够简单,但足够复杂,可以给出信息性的、意想不到的结果。生态系统是极其复杂的,生态学家一直在寻求以现实的方式对这些系统进行建模的方法。这个项目是对使用新开发的计算机技术的建模方法的重大贡献,这是人工智能方法的跨学科应用。这一方法可能是在现实生态环境中理解重要问题的有力手段,例如种群和栖息地的保护或气候变化等长期动态模式。&;(u&;G(`I M&;G()I M“&;!!!F N N(Times New Roman符号&;Arial“h;e;e;e 9 i 1 Deborah Johnson Deborah Johnson
英文摘要
9314432 Starfield This research project will develop a paradigm for simulating dynamics of ecological systems. the paradigm models the different states of the systems separately, using the syntax of frames as borrowed from Artificial Intelligence. Within each frame, simple models (either numerical or qualitative) simulate the key processes for the corresponding ecological state. "Demons" watch to see whether the assumptions underlying the definition of the state are transgressed, and if so, switch to a different model in a different frame. This approach greatly facilitates the process of building dynamic ecosystem models. It makes it possible to rapidly test hypotheses, and leads to models that are easy to understand and therefore facilitates the communication of ideas. It also lends itself to models which include interactions between ongoing process (such as competition and herbivory and sporadic events (such as fires) at a level of resolution that is simple enough to comprehend but sufficiently complex to give informative unanticipated results. %%% Ecological systems are exceedingly complex and ecologist have been pursuing ways to model these systems in realistic ways. This project is a substantial contribution to the modeling approach using newly developed computer technology that is an interdisciplinary application of methods in Artificial Intelligence. This approach could be a powerful means of understanding important issues, such as conservation of populations and habitats or long-term dynamic patterns such as climate change, in realistic ecological contexts. & ( u & G(` i M & G( ) i M " & ! ! ! F N N ( Times New Roman Symbol & Arial " h ; e ; e ; e 9 I 1 Deborah Johnson Deborah Johnson
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
Collaborative Research: Climate and the Expansion of the Boreal Forest at Latitudinal Treeline: A Field-and Model-Based Investigation
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批准号:9732057
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项目类别:Continuing Grant
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资助金额:$4.78万
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财政年份:1998
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负责人:Anthony Starfield
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依托单位:
Effect of Treeline Movement in the Alaskan Arctic on Global Climate Change
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批准号:9630913
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项目类别:Standard Grant
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资助金额:$39.07万
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财政年份:1996
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负责人:Anthony Starfield
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依托单位:
国内基金
海外基金
精子发生中mRNA下游开放阅读框(downstream Open Reading Frame,dORF)的功能研究
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批准号:--
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项目类别:面上项目
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资助金额:54万元
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批准年份:2022
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负责人:刘明兮
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依托单位:
非线性框架(Frame)表现及字典学习与神经网络的非梯度反向传播学习算法
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批准号:62076077
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项目类别:面上项目
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资助金额:59.0万元
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批准年份:2020
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负责人:丁数学
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依托单位:
非线性框架(Frame)表现及字典学习与神经网络的非梯度反向传播学习算法
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批准号:--
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项目类别:--
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资助金额:59万元
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批准年份:2020
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负责人:丁数学
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依托单位: