中国电力2024，Vol.57Issue(5)：251-260,10.DOI:10.11930/j.issn.1004-9649.202303125
基于嵌入法与集成学习的线路工程造价预测
Prediction of Transmission Line Cost Based on Embedding Method and Ensemble Learning
摘要
Abstract
Accurate prediction of transmission line project cost is of great significance to construction quality and cost control.Since the feature dimension in the traditional transmission line project cost prediction is too high and a single prediction model is difficult to fit the complex cost data,a transmission line project cost prediction method is proposed based on embedding dimensionality reduction and ensemble learning.Firstly,the features are sorted with the embedding method and the XGBoost model to screen out the features that have a significant impact on the cost,achieving the data dimensionality reduction.Then the XGBoost,random forest,SVM and other models are integrated to form a two-layer ensemble learning model.Finally,a case study is carried out based on the data of real transmission line projects,and the proposed method is compared with the XGBoost,random forest,SVM,ELM,and BP neural network models.The rusults show that the mean absolute percentage error of the proposed method is within 4%,which is superior to other single model,and is of great value to the research of transmission line project cost control.关键词
输电线路/造价预测/集成学习/数据降维/嵌入法Key words
transmission line/cost prediction/ensemble learning/dimensionality reduction/embedding method引用本文复制引用
叶煜明,钱琪琪,万正东,张继钢..基于嵌入法与集成学习的线路工程造价预测[J].中国电力,2024,57(5):251-260,10.基金项目
中国南方电网有限责任公司科技项目(面向造价智能化管控的数据分析与应用策略研究,ZBKJXM2022 0003). This work is supported by Science and Technology Project of China Southern Power Grid Co.,Ltd.(Research on Data Analysis and Application Strategy for Intelligent Cost Management and Control,No.ZBKJXM20220003). （面向造价智能化管控的数据分析与应用策略研究,ZBKJXM2022 0003）
