NEURG-PUZZY PHILLIPS-TYPE POLICY MODELS FOR FISCAL AND MONETARY DECISION-MAKERS

机译：Neurg-Pulzy Phillips型政策模式为财政和货币决策者

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The purpose of this paper is to consider applicability and theoretical framework of the Neuro-fuzzy Phillips-type PID stabilization policy with genetic algorithm for decentralized fiscal and monetary decision makers under hierarchical policy structure with the upper level policy-coordinator. This policy is formulated by the Phillips-type stabilization policy problem consisting of feedback rule policies with varying the feedback gain parameters leading to the desired targets subject to the econometric models characterized by the respective fiscal and monetary decision-makers. In order to compute the feedback gain coefficients, the neural networks algorithm after selecting some policy rules by genetic algorithm are used.

机译：本文的目的是考虑与上层政策结构下的分散财政和货币决策者的遗传算法，以较高级政策 - 协调员在分层政策结构下考虑神经模糊菲利普斯型PID稳定政策的适用性和理论框架。该策略由Phillips型稳定策略问题组成，该稳定策略问题由反馈规则策略组成，该策略具有改变导致所需目标的反馈增益参数，该参数受到各个财政和货币决策者的特征的计量计量的所需目标。为了计算反馈增益系数，使用了通过遗传算法选择一些策略规则之后的神经网络算法。

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来源
《IFAC Multitrack Conference on Advanced Control Strategies for Social and Economic Systems》|2005年||共6页
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作者
Yukio Ito;
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原文格式 PDF
正文语种
中图分类 TP273-53;
关键词
Fuzzy control; neural networks; genetic algorithms; PID control; economic systems;

机译：模糊控制;神经网络;遗传算法;PID控制;经济系统;

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NEURG-PUZZY PHILLIPS-TYPE POLICY MODELS FOR FISCAL AND MONETARY DECISION-MAKERS

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