电网企业财务健康诊断知识推理技术

Knowledge inference techniques for financial health diagnosis of power grid enterprises

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。

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 diagnosis methods, organically 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.