Knowledge inference techniques for financial health diagnosis of power grid enterprises

Qiming WAN; Yingjun WANG; Youhua LI

doi:10.11959/j.issn.1000−0801.2018148

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Knowledge inference techniques for financial health diagnosis of power grid enterprises

Operation and wide Angle | 更新时间：2024-06-05

- Knowledge inference techniques for financial health diagnosis of power grid enterprises
- Telecommunications Science Vol. 34, Issue 8, Pages: 186-192(2018)
- 作者机构：
  
  1. 北京中电普华信息技术有限公司，北京100192
  2. 国网能源研究院有限公司，北京102209
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.1000−0801.2018148
  CLC： TP391.5
- Published Online：2018-08，
  
  Published：20 August 2018
- 稿件说明：
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Qiming WAN, Yingjun WANG, Youhua LI. Knowledge inference techniques for financial health diagnosis of power grid enterprises[J]. Telecommunications science, 2018, 34(8): 186-192.
DOI：

Qiming WAN, Yingjun WANG, Youhua LI. Knowledge inference techniques for financial health diagnosis of power grid enterprises[J]. Telecommunications science, 2018, 34(8): 186-192. DOI： 10.11959/j.issn.1000−0801.2018148.

摘要

研究了电网企业财务健康诊断知识推理技术，将专家系统与神经网络相结合，采用专家系统框架，利用神经网络完成部分知识的存储与表示，克服了传统诊断方法的局限性，将领域专家的知识与神经网络的自学习能力有机融合在一起，实现对电网企业财务更健康、更准确的实时状态检测与智能诊断。

Abstract

The knowledge inference techniques for financial health diagnosis of power grid enterprises was studied.Combining experts system with neural network

expert system framework was used

finishing storage and representation of partial knowledge with neural network

thus overcoming the limitations of traditional diagnosismethods

organi cally integrating experts’knowledge in the field with self-learning abilities of neutral network.More accurate real-time status detection and intelligent diagnosis for financial health of power grid enterprise were realized.

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references

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