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A Fuzzy Cognitive Map Approach to Investigate the Sustainability of the Social Security System in Jordan

机译:一种探讨约旦社会保障制度可持续性的模糊认知地图方法

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Fuzzy Cognitive Maps are emerging as an important new tool in economic modelling. The aim of this study is to investigates the use of fuzzy cognitive maps with their learning algorithms, based on genetic algorithms, for the purposes of prediction of economic sustainability. A Case study data are extracted from the Jordanian Social Security system for the last 120 months; The Real-Code genetic algorithm and structure optimization algorithm were chosen for their ability to select the most significant relationships between the concepts and to predict future development of the Jordanian social security revenues and expenses. The study shows that fuzzy cognitive maps models clearly predict the future of a complex financial system with incoming and outgoing flows. Therefore, this research confirms the benefits of fuzzy cognitive maps applications as a tool for scholarly researchers, economists and policy makers.
机译:模糊认知地图正在成为经济建模中的重要新工具。 本研究的目的是根据经济可持续性的预测来调查基于遗传算法的基于遗传算法的模糊认知地图使用模糊认知地图。 案例研究数据在过去120个月中从约旦社会保障系统中提取; 选择了实际码遗传算法和结构优化算法,以便他们选择概念之间最重要的关系和预测约旦社会保障收入和费用的未来发展。 该研究表明,模糊认知地图模型清楚地预测了传入和传出流动的复杂金融系统的未来。 因此,本研究证实了模糊认知地图应用的好处作为学术研究人员,经济学家和政策制定者的工具。

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