气膜钢筋混凝土主体结构施工成本预测研究

发布时间：2018-03-20 09:35

本文选题：气膜钢筋混凝土结构　切入点：施工成本　出处：《河北工程大学》2017年硕士论文　论文类型：学位论文

【摘要】：气膜钢筋混凝土结构是我国近年来从国外引进并大力推广的一种新型建筑结构形式,在其项目管理中,对该结构主体部分的施工成本进行快速精确预测有着重要意义。本文引入粒子群算法(PSO)和极限学习机(ELM)相结合的方法,对气膜钢筋混凝土主体结构施工成本的预测进行了研究。首先,根据气膜钢筋混凝土主体结构的结构特点,分析影响其施工成本的因素,建立该结构的施工成本预测指标体系;其次,运用PSO算法对ELM的输入权值和隐含层阈值进行优化,构建了基于PSO-ELM的施工成本预测模型;最后,通过气膜钢筋混凝土主体结构施工成本数据进行预测仿真,结果显示PSO-ELM比ELM模型精确度更高,是预测气膜钢筋混凝土主体结构施工成本的一种科学、有效的方法。
[Abstract]:The air-film reinforced concrete structure is a new type of building structure which has been introduced and popularized from abroad in recent years in our country. It is of great significance to predict the construction cost of the main part of the structure quickly and accurately. In this paper, the Particle Swarm Optimization (PSO) and the extreme Learning Machine (ELM) are introduced. In this paper, the construction cost prediction of the air-film reinforced concrete main structure is studied. Firstly, according to the structural characteristics of the air-film reinforced concrete main structure, the factors affecting the construction cost are analyzed, and the construction cost prediction index system of the structure is established. Secondly, the input weight and hidden layer threshold of ELM are optimized by PSO algorithm, and the construction cost prediction model based on PSO-ELM is constructed. The results show that PSO-ELM is more accurate than ELM model, and it is a scientific and effective method to predict the construction cost of air-film reinforced concrete structure.
【学位授予单位】：河北工程大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TU723.3

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