Predicting the Future: Completing Models of Observed Complex Systems
Predicting the Future: Completing Models of Observed Complex Systems
复制标题
预测未来：完成观察到的复杂系统的模型
DOI：
10.1007/978-1-4614-7218-6
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发表时间：
2013
期刊：
影响因子：
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通讯作者：
H. Abarbanel
中科院分区：
文献类型：
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作者：
H. Abarbanel
通过开发用于将信息从观测传递到被观测系统模型的精确路径积分，作者为讨论跨学科的模型建立和评估提供了一般框架。通过从神经科学、地球科学和非线性电路模型中提取的许多说明性例子，详细地例证了这些概念。探索了路径积分近似计算的实用数值方法，并探讨了它们在设计实验和确定模型与观测值一致性方面的应用。
Through the development of an exact path integral for use in transferring information from observations to a model of the observed system, the author provides a general framework for the discussion of model building and evaluation across disciplines. Through many illustrative examples drawn from models in neuroscience, geosciences, and nonlinear electrical circuits, the concepts are exemplified in detail. Practical numerical methods for approximate evaluations of the path integral are explored, and their use in designing experiments and determining a models consistency with observations is explored.