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ENCODING AND USING DOMAIN KNOWLEDGE ON POPULATION DYNAMICS FOR EQUATION DISCOVERY

机译:对等式发现人口动态的编码和使用域知识

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This chapter is concerned with integrating knowledge-based modeling or modeling from first principles, with data-driven or automated modeling of dynamic systems. The approach presented here includes methods for equation discovery: Unlike mainstream system identification methods, which work under the assumption that the form of the equations is known, equation discovery systems explore a space of possible equation structures. We propose a formalism for representing knowledge about processes in population dynamics domains and a method to transform such knowledge into an operational form that could be used by equation discovery systems. We also describe the extensions of the equation discovery system LAGRAMGE necessary to incorporate this kind of knowledge in the process of equation discovery.
机译:本章涉及从第一原理集成基于知识的建模或建模,具有动态系统的数据驱动或自动建模。这里呈现的方法包括用于等式发现的方法:与主流系统识别方法不同,在假设已知方程式的形式之下,等式发现系统探索可能的等式结构的空间。我们提出了一种形式主义,用于代表有关人口动态域的过程的知识以及将这些知识转换为可由等式发现系统可以使用的操作形式的方法。我们还描述了在等式发现过程中结合这种知识所必需的等式发现系统LAGRAME的扩展。

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