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Chaos and Complex in Measuring Sustainability of Economic Condition in Indonesia

机译:衡量印度尼西亚经济状况可持续性的混沌和复杂

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Economic indicator in Indonesia are GDP (Gross Domestic Product), GNI (Gross National Income), inflation, export and import. These data had been chosen because economic that came from words 'ecos' and 'nomos' consist of value of life which are implemented in them. Based on that reason, it cannot be avoided that chaos and complex will emerge during measure the economic condition. In order to monitor Indonesia's economic, system that predict each of economic indicator had been developed. This concept tried to answer the chaos and complex in real-problem. System did not measure only one indicator independently, instead of involve all of indicators while predict it. So that, non-linear differential dynamic had been used to face this issued. Furthermore, system would predict as time series and optimized using genetic algorithm. By setting parameter probability mutation and probability cross over, this research got accuracy around 30% 80%. The range of accuracy proved that the system able enough to fit data in finding historical pattern even had to face with chaos and complex. Distribution data and non-linear differential equation are caused of chaos and complex respectively.
机译:印度尼西亚经济指标是GDP(国内生产总值),GNI(国民总收入),通货膨胀,出口和进口。这些数据已被选中,因为来自“ECO”和“Nomos”的经济,由在其中实施的生活价值组成。根据这一原因,在衡量经济条件时,不能避免混乱和复合物。为了监测印度尼西亚的经济,制定预测每个经济指标的系统。这个概念试图在实际问题中回答混乱和复杂。系统没有独立测量一个指示器,而不是涉及所有指示符,而预测它。因此,非线性差动动态已被用来面对这一发布。此外,系统将预测时间序列并使用遗传算法优化。通过设定参数概率突变和概率交叉,这项研究得到了约30%的准确性80%。准确性的范围证明,系统能够足以满足历史模式的数据,甚至必须面对混乱和复杂。分布数据和非线性微分方程分别是混沌和复杂的。

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