荷兰非寿险公司评价的神经网络模型

Proceedings 1995 Second New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems Pub Date : 1995-11-20 DOI:10.1109/ANNES.1995.499499

B. Kramer

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引用次数: 0

摘要

基于六项财务比率，一个单隐藏层反向传播神经网络将荷兰非寿险公司划分为强、中、弱。该网络对弱公司和强公司的表现都很好(95%的正确率)，但对中等公司的识别却完全失败。通过计算每个输入变量和每个输出变量之间的关系强度来分析每个输入变量的相对重要性。

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A neural network model for the evaluation of Dutch non-life insurance companies

Based on six financial ratios, a one-hidden-layer back-propagation neural network classifies Dutch non-life insurance companies as strong moderate, or weak. The network shows very good performance for weak and strong companies (95% correct), but completely fails to recognize moderate companies. The relative importance of each input variable is analyzed by calculating the strength of the relationship between each input and each output variable.

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Proceedings 1995 Second New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems

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