数据挖掘和神经网络技术在电力工程造价应用

Application of data mining and neural network technology in electric power engineering cost

旨在探索数据挖掘和神经网络技术在电力工程造价的实际应用,利用数据挖掘和神经网络技术创建电力工程造价审计的理论模型,在数据挖掘技术的作用下,完成数据预处理以及属性优选的相关工作,继而剖离出数据挖掘技术的模糊规则,并通过神经网络技术重构电力工程造价的预测方法。结论表明数据挖掘和神经网络技术可提高电力工程造价预测与审查的准确性。

This paper explores the data mining and neural network technology in the practical application of electric power engineering cost, using data mining and neural network technology to create the theoretical model of electric power engineering cost audit, under the function of data mining technology, data preprocessing and attribute optimization of relevant work, which in turn cause from the data mining technology of fuzzy rules, by reconstructing neural network technology and the electric power engineering cost prediction method. Conclusion indicates that data mining and neural network technology can improve the accuracy of the electric power engineering cost forecast and review.