基于ANN算法的钢结构安装工程质量状态评价

Quality State Evaluation of Steel Structure Installation Engineering Based on ANN Algorithm

随着石油建设工程项目规模越来越大,对钢结构安装工程的要求越来越高,钢结构安装工程质量检测与评价更加复杂,这些特点使得在施工现场对钢结构安装质量状态评价方法不一、结果也不易控制。为了对钢结构安装工程质量评价更加准确、适用,在人工神经网络(ANN)算法的基础上对钢结构安装工程质量评价方法进行了研究,并采用BP神经网络和RBF神经网络算法进行对照实验,梳理质量评价指标,计算其权重系数并进行误差分析,由实验结果选定ANN算法来得出钢结构安装工程质量状态的评分公式,以反映钢结构安装工程的质量情况,对钢结构安装工程的质量把控和管理有一定的指导作用,为工程质量管理和控制提供科学、准确的支持。

With the increasing scale of petroleum construction projects,the requirements for steel structure installation projects are higher and higher,and the quality detection and evaluation of steel structure installation projects are more complicated,and these characteristics make the evaluation methods of steel structure installation quality status at the construction site vary and the results are not easy to control.In order to evaluate the quality of steel structure installation project more accurately and applicable,the quality evaluation method of steel structure installation project is studied on the basis of artificial neural network(ANN)algorithm,and BP neural network and RBF neural network algorithms are used to conduct comparative experiments,sort out the quality evaluation indexes,compute the weight coefficients and carry out error analysis,and ANN algorithm is selected to derive the scoring formula of the quality status of steel structure installation project from the experimental results,to reflect the quality of the steel structure installation project,which has a certain guiding effect on the quality control and management of the steel structure installation project,providing scientific and accurate support for engineering quality management and control.