使用智能系统的社会转型建模

IF 2.6 3区数学 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS

Journal of Systems Science & Complexity Pub Date : 2008-10-11 DOI:10.1109/CANS.2008.8

H. Owladeghaffari, W. Pedrycz, M. Sharifzadeh

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引用次数: 1

摘要

在这项研究中，我们重现了两个新的混合智能系统，涉及三种著名的智能计算和近似推理方法:自组织特征映射(SOM)，神经模糊推理系统和粗糙集理论(RST)，称为SONFIS和SORST。我们展示了如何将我们的算法解释为政府-社会(或任何其他类似系统)相互作用的联系，其中政府捕获各种行为状态:不稳定(绝对)或灵活状态。因此，通过连接参数(噪声)从有序到无序的变化，可以推断出社会的过渡。

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查看原文本刊更多论文

Modeling of Social Transitions Using Intelligent Systems

In this study, we reproduce two new hybrid intelligent systems, involve three prominent intelligent computing and approximate reasoning methods: Self Organizing feature Map (SOM), Neuro-Fuzzy Inference System and Rough Set Theory (RST), called SONFIS and SORST. We show how our algorithms can be construed as a linkage of government-society (or any other similar systems) interactions, where government catches various states of behaviors: ldquosolid (absolute) or flexiblerdquo. So, transition of society, by changing of connectivity parameters (noise) from order to disorder is inferred.

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来源期刊

Journal of Systems Science & Complexity 数学-数学跨学科应用

CiteScore

3.80

自引率

9.50%

发文量

审稿时长

6-12 weeks

期刊介绍： The Journal of Systems Science and Complexity is dedicated to publishing high quality papers on mathematical theories, methodologies, and applications of systems science and complexity science. It encourages fundamental research into complex systems and complexity and fosters cross-disciplinary approaches to elucidate the common mathematical methods that arise in natural, artificial, and social systems. Topics covered are: complex systems, systems control, operations research for complex systems, economic and financial systems analysis, statistics and data science, computer mathematics, systems security, coding theory and crypto-systems, other topics related to systems science.