Modeling of Social Transitions Using Intelligent Systems

TL;DR

This paper introduces hybrid intelligent systems combining SOM, Neuro-Fuzzy, and RST to model societal transitions influenced by government interactions, demonstrating how societal states shift from order to disorder through parameter changes.

Contribution

The paper presents two novel hybrid systems, SONFIS and SORST, integrating multiple intelligent methods to model complex social transitions and government-society dynamics.

Findings

Systems can infer societal state transitions from order to disorder.

Hybrid models effectively link government actions to societal behavior.

Parameter changes simulate societal flexibility and rigidity.

Abstract

In this study, we reproduce two new hybrid intelligent systems, involve three prominent intelligent computing and approximate reasoning methods: Self Organizing feature Map (SOM), Neruo-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 interactions, where government catches various states of behaviors: solid (absolute) or flexible. So, transition of society, by changing of connectivity parameters (noise) from order to disorder is inferred.