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估计自然法则和数据驱动模型的综合方法:以排列网络为例

A hybrid approach of physical laws and data-driven modeling for estimation: the example of queuing networks

作者:Aude Hofleitner 作者单位:University of California at Berkeley 加工时间:2013-11-24 信息来源:EECS 索取原文[212 页]
关键词:数学模型;估计;市区运输网络
摘 要:Mathematical models are a mathematical abstraction of the physical reality which is of great importance to understand the behavior of a system, make estimations and predictions and so on. They range from models based on physical laws to models learned empirically, as measurements are collected, and referred to as data-driven models. A model is based on a series of choices which in uence its complexity and realism. These choices represent tradeo s between di erent competing objectives including interpretability, scalability, accuracy, adequation to the available data, robustness or computational complexity. The thesis investigates the advantages and disadvantages of models based on physical laws versus data-driven models through the example of signalized queuing networks such as urban transportation networks.
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