基于DBO-RBF的建筑工程成本估算模型  

Architectural engineering cost estimation model based on DBO-RBF

作　　者：杨文才 YANG Wencai(Yongdao Engineering Consulting Co.,Ltd.,Guangzhou 510000,China)

机构地区：[1]永道工程咨询有限公司,广东广州510000

出　　处：《无线互联科技》2025年第6期96-99,共4页Wireless Internet Science and Technology

摘　　要：为了实现建筑工程成本的精准估算,文章提出一种基于蜣螂优化(Dung Beetle Optimization,DBO)算法优化径向基函数(Radial Basis Function,RBF)神经网络的建筑工程成本估算方法。该研究利用DBO算法寻优搜索确定RBF神经网络的最优网络参数。在此基础上构建DBO-RBF模型,文章利用DBO-RBF模型对实际工程的建筑成本进行估算,将估算结果与其他方法对比。结果表明,DBO-RBF模型输出结果的均方根误差和平均相对误差分别为121.48万元和3.24%,在模型稳定性和估算精度方面优于其他对比方法,验证了所提方法的有效性。In order to achieve accurate estimation of architectural engineering project cost,the article proposes a architectural engineering project cost estimation method based on Dung Beetle Optimization(DBO)algorithm to optimize Radial Basis Function(RBF)neural network.This study uses the DBO algorithm to search and determine the optimal network parameters of the RBF neural network.Based on this,a DBO-RBF model is constructed,and the actual construction cost of the project is estimated using the DBO-RBF model.The estimation results are compared with other methods,and the results shows that the root mean square error and average relative error of the output results of the DBO-RBF model are 1.2148 million yuan and 3.24%,respectively,which are superior to other comparison methods in terms of model stability and estimation accuracy,verifying the effectiveness of the proposed method in this article.

关 键 词：建筑工程 成本 估算 径向基函数神经网络 蜣螂优化算法 

分 类 号：TP311.52[自动化与计算机技术—计算机软件与理论]