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A Web-based Tool for Identifying Strategic Intervention Points in Complex Systems

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abstract

Steering a complex system towards a desired outcome is a challenging task. The lack of clarity on the system's exact architecture and the often scarce scientific data upon which to base the operationalisation of the dynamic rules that underpin the interactions between participant entities are two contributing factors. We describe an analytical approach that builds on Fuzzy Cognitive Mapping (FCM) to address the latter and represent the system as a complex network. We apply results from network controllability to address the former and determine minimal control configurations - subsets of factors, or system levers, which comprise points for strategic intervention in steering the system. We have implemented the combination of these techniques in an analytical tool that runs in the browser, and generates all minimal control configurations of a complex network. We demonstrate our approach by reporting on our experience of working alongside industrial, local-government, and NGO stakeholders in the Humber region, UK. Our results are applied to the decision-making process involved in the transition of the region to a bio-based economy.

fields

cs.AI 1

years

2019 1

verdicts

UNVERDICTED 1

representative citing papers

Customer Segmentation of Wireless Trajectory Data

cs.AI · 2019-06-20 · unverdicted · novelty 4.0

A semantic trajectory clustering approach for non-geographic wireless data is introduced and tested on incomplete London Underground commute trajectories, finding varied patterns without distinct clusters.

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  • Customer Segmentation of Wireless Trajectory Data cs.AI · 2019-06-20 · unverdicted · none · ref 24 · internal anchor

    A semantic trajectory clustering approach for non-geographic wireless data is introduced and tested on incomplete London Underground commute trajectories, finding varied patterns without distinct clusters.