TL;DR
This paper introduces MACIPS, a framework modeling complex societal interactions using connected intelligent particles, and explores phase transitions from order to disorder influenced by connectivity parameters, with applications to financial systems.
Contribution
It presents a novel framework (MACIPS) combining intelligent computing methods to model societal and financial phase transitions based on connectivity changes.
Findings
Demonstrates phase transition behavior in MACIPS models.
Links societal behavior changes to connectivity parameters.
Suggests applications to financial market fluctuations.
Abstract
In this study, we introduce general frame of MAny Connected Intelligent Particles Systems (MACIPS). Connections and interconnections between particles get a complex behavior of such merely simple system (system in system).Contribution of natural computing, under information granulation theory, are the main topics of this spacious skeleton. Upon this clue, we organize two algorithms involved a few prominent intelligent computing and approximate reasoning methods: self organizing feature map (SOM), Neuro- Fuzzy Inference System and Rough Set Theory (RST). Over this, we show how our algorithms can be taken as a linkage of government-society interaction, where government catches various fashions of behavior: solid (absolute) or flexible. So, transition of such society, by changing of connectivity parameters (noise) from order to disorder is inferred. Add to this, one may find an indirect…
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