论文标题

部分可观测时空混沌系统的无模型预测

Lupascian Non-Negativity Applied to Conceptual Modeling: Alternating Static Potentiality and Dynamic Actuality

论文作者

Al-Fedaghi, Sabah

论文摘要

储层计算是预测湍流的有力工具,其简单的架构具有处理大型系统的计算效率。然而,其实现通常需要完整的状态向量测量和系统非线性知识。我们使用非线性投影函数将系统测量扩展到高维空间,然后将其输入到储层中以获得预测。我们展示了这种储层计算网络在时空混沌系统上的应用,该系统模拟了湍流的若干特征。我们表明,使用径向基函数作为非线性投影器,即使只有部分观测并且不知道控制方程,也能稳健地捕捉复杂的系统非线性。最后,我们表明,当测量稀疏、不完整且带有噪声,甚至控制方程变得不准确时,我们的网络仍然可以产生相当准确的预测,从而为实际湍流系统的无模型预测铺平了道路。

In software engineering, conceptual modeling focuses on creating representations of the world that are as faithful and rich as possible, with the aim of guiding the development of software systems. In contrast, in the computing realm, the notion of ontology has been characterized as being closely related to conceptual modeling and is often viewed as a specification of a conceptualization. Accordingly, conceptual modeling and ontology engineering now address the same problem of representing the world in a suitable fashion. A high-level ontology provides a means to describe concepts and their interactions with each other and to capture structural and behavioral features in the intended domain. This paper aims to analyze ontological concepts and semantics of modeling notations to provide a common understanding among software engineers. An important issue in this context concerns the question of whether the modeled world might be stratified into ontological levels. We introduce an abstract system of two-level domain ontology to be used as a foundation for conceptual models. We study the two levels of staticity and dynamics in the context of the thinging machine (TM) model using the notions of potentiality and actuality that the Franco-Romanian philosopher Stephane Lupasco developed in logic. He provided a quasi-universal rejection of contradiction where every event was always associated with a no event, such that the actualization of an event entails the potentialization of a no event and vice versa without either ever disappearing completely. This approach is illustrated by re-modeling UML state machines in TM modeling. The results strengthen the semantics of a static versus dynamic levels in conceptual modeling and sharpen the notion of events as a phenomenon without negativity alternating between the two levels of dynamics and staticity.

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