基于神经网络的观测数据修正

Proceedings of ICSSSM '05. 2005 International Conference on Services Systems and Services Management, 2005. Pub Date : 2005-06-13 DOI:10.1109/ICSSSM.2005.1500168

Yong Wu, Y. Wang, Xiangwei Liu, Jianmin Zhong

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引用次数: 0

摘要

在编制死亡率表时，对观测数据进行分类是一项非常重要的工作。目前，影响毕业方法的局限性是多方面的。本文采用神经网络来完成数据的修正。本文主要采用三比八比一的神经网络模型对观测数据进行分度。结果表明，该方法是正确的，并可推广到其它方案观测数据的分度。

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Revision of the observed data based on neural networks

It is a very important task for graduation of the observed data in composing the mortality table. Currently, there are different limitations influencing the methods of graduation. In this paper, the revision of data is completed by means of neural networks. This paper mainly uses a three -to -eight -to -one's model of neural network for graduation of the observed data. As it is illustrated in the paper, the method is right, and can be generalized to the graduation of observed data of other schemes.

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Proceedings of ICSSSM '05. 2005 International Conference on Services Systems and Services Management, 2005.

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