基于BP神经网络与BIM的电网工程数据处理方法研究

Research on data processing method of power network engineering based on BP neural network and BIM

针对当前输变电工程数据量急剧增加,给工程管理带来严峻挑战的现状,提出了一套基于BP神经网络与BIM的智能化输变电工程数据处理方法。该方法在设计BP神经网络算法模型的基础上,构建了数据预处理算法流程,并实现了基于BIM模型的输变电工程数据库架构。同时将关键因素作为样本数据对BP神经网络进行训练,进而实现对输变电工程数据的分解及预测。以实际输变电工程数据集作为样本进行了仿真实验分析,结果表明,文中所提算法的输变电工程成本预测均小于5%,相比于传统的统计分析方法,其具有更高的准确性,且能够为工程造价预测提供有效的数据支撑。

In view of the current situation that the rapid increase in the amount of data of power transmission and transformation project brings severe challenges to the project management,an intelligent data processing method for power transmission and transformation engineering based on BP neural network and BIM is proposed.Based on the design of BP neural network algorithm model,the data preprocessing algorithm process is constructed,and the database architecture of power transmission and transformation project based on BIM model is constructed.Taking the key factor data as the sample data,the BP neural network is trained to realize the data decomposition and prediction of power transmission and transformation project.Taking the actual power transmission and transformation project data set as a sample,the simulation experiment analysis is carried out.The results show that the cost prediction of power transmission and transformation project by the proposed algorithm is less than 5%.Compared with the traditional statistical analysis method,it has higher accuracy and can provide effective data support for project cost prediction.