基于WLCS-ALA模型的建设项目投资估算研究

发布时间：2018-07-26 20:59

【摘要】：当前建设项目投资迅速增长,为我国国民经济发展提供了良好环境,但投资控制情况不甚理想。主要原因是现行的造价估算方法多采用线性方法,准确性较低,并不能反映出造价和影响因素之间的不确定性和非线性关系。人工生命进化算法具有较高的全范围搜寻能力,通过迭代可以获得较精确的全局优化值,其具有的不确定性、非线性、自组织、自学习、自进化等特征能够有效拟合投资估算复杂系统。结合全生命显著性造价理论和人工生命进化算法理论,建立WLCS-ALA模型,尝试将人工生命算法应用于造价投资预测问题,运用全生命显著性造价模型(WLCS)简化数据处理量,通过计算与拟建项目类似的已完工程的显著性造价历史数据,建立显著性成本项目(CSIs)和显著性因子数据序列,采用人工生命算法(ALA)进行数据优化,寻求优化造价。通过案例实证分析,采用WLCS-ALA模型估算的单位造价精确度远高于传统方法,说明在投资决策领域应用人工生命进化方法会使投资预测更加精确,从而验证了本模型的有效性和准确性。
[Abstract]:The rapid growth of investment in construction projects has provided a good environment for the development of our national economy, but the situation of investment control is not very satisfactory. The main reason is that most of the current cost estimation methods use linear method, and the accuracy is low, which can not reflect the uncertainty and nonlinear relationship between the cost and the influencing factors. The artificial life evolution algorithm has a high searching ability in the whole range. It can get more accurate global optimization value by iteration. It has uncertainty, nonlinearity, self-organization, self-learning. The characteristics such as self-evolution can fit the complex system of investment estimation effectively. Combined with the theory of the whole life significance cost and the artificial life evolution algorithm, the WLCS-ALA model is established. The artificial life algorithm is applied to the cost investment prediction problem, and the whole life significance cost model (WLCS) is used to simplify the data processing capacity. By calculating the significant cost historical data of the completed project similar to the planned project, the significant cost item (CSIs) and significant factor data sequence are established, and the artificial life algorithm (ALA) is used to optimize the data to optimize the cost. Through the empirical analysis of cases, the accuracy of estimating unit cost by using WLCS-ALA model is much higher than that of traditional method, which shows that the application of artificial life evolution method in the field of investment decision-making will make investment prediction more accurate. The validity and accuracy of the model are verified.
【作者单位】：石家庄铁道大学经济管理学院;河北地质大学;
【基金】：2011年度教育部人文社会科学研究规划基金(11YJAZH121)
【分类号】：F285

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