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铁矿石境外投资风险评估的模糊神经网络模型

A Fuzzy Neural Network Model of Overseas Iron Ore Investment Risk Assessment
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摘要 论文将模糊理论与神经网络结合,对铁矿石境外投资所涉及的风险因素分别从资产影响、威胁频度两方面进行分析,建立了铁矿石境外投资的风险层次化结构,并构造了各因素所对应评判集的隶属度矩阵;综合运用模糊推理算法与神经网络仿真技术,对铁矿石境外投资的风险进行评估,进而判定铁矿石境外投资风险等级。最后,通过计算铁矿石境外投资的市场风险说明了算法的应用,并将结果与模糊综合评估得到的风险值进行比较,检测了模型的有效性。 Based on the theory of risk assessment,this paper firstly analyzed the risk from the asset influence and frequency of threat,set up risk level structure of overseas iron ore investment,and presented the membership matrices for judgment set.Then,the neural network and fuzzy reasoning theory were applied to evaluate the risk of overseas iron ore investment to obtain its risk grade. Finally,by calculating the market risk of overseas iron ore investment shown how the method works,and the error analysis was applied to detecting effectiveness and reliability of the model performance.
出处 《微计算机信息》 2012年第2期17-18,150,共3页 Control & Automation
关键词 模糊神经网络 铁矿石 境外投资 风险评估 fuzzy neural network iron ore investment risk oversea risk assessment
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