State-of-the-Art Development of Complex Systems and Their Simulation Methods

Yiming Tang;Lin Li;Xiaoping Liu
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引用次数: 1

Abstract

The research on complex systems is different from that on general systems because the former must consider self-organization, emergence, uncertainty, predetermination, and evolution. As an important method to transform the world, a simulation is one of the most important skills to discover complex systems. In this study, we provide a survey on complex systems and their simulation methods. Initially, the development history of complex system research is summarized from two main lines. Then, the eight common characteristics of the most complex systems are presented. Furthermore, the simulation methods of complex systems are introduced in detail from four aspects, namely, meta-synthesis methods, complex networks, intelligent technologies, and other methods. From the overall point of view, intelligent technologies are the driving force, and complex networks are the advanced structure. Meta-synthesis methods are the integration strategy, and other methods are the supplements. In addition, we show three complex system simulation examples: digital reactor simulation, simulation of a logistics system in the industrial site, and crowd evacuation simulation. The examples show that a simulation is a useful means and an important method in complex system research. Finally, the future development prospects for complex systems and their simulation methods are suggested.
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复杂系统的最新发展及其仿真方法
复杂系统的研究不同于一般系统的研究,复杂系统的研究必须考虑自组织、涌现、不确定性、预定和演化等问题。仿真作为一种改造世界的重要方法,是发现复杂系统的重要技能之一。在本研究中,我们对复杂系统及其仿真方法进行了综述。本文首先从两条主线总结了复杂系统研究的发展历史。然后,给出了最复杂系统的八个共同特征。从元综合方法、复杂网络、智能技术和其他方法四个方面详细介绍了复杂系统的仿真方法。从整体上看,智能技术是动力,复杂网络是先进结构。综合方法是整合策略,其他方法是补充策略。此外,我们还展示了三个复杂系统仿真示例:数字反应堆仿真、工业现场物流系统仿真和人群疏散仿真。实例表明,仿真是复杂系统研究的一种有效手段和重要方法。最后,对复杂系统及其仿真方法的发展前景进行了展望。
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7.80
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