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A MODEL FOR CONSTRUCTION PROJECT BUDGET AND SCHEDULE PERFORMANCES USING FUZZY DATA

机译:基于模糊数据的工程项目预算与进度绩效模型

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摘要

Ensuring satisfactory budget and schedule performance are two major challenges for construction projects. On this issue, predictive models for budget and schedule performances can provide assistance in the appropriate allocation of project management resources. Two neural network models for construction budget and schedule performances using fuzzy data have been developed in the present study. These models consist of eight and five key determinants of project outcome, respectively. A combined fuzzy index (CFI) approach is introduced for data representation. The CFI for an input or output measurement can be derived using the fuzzy number membership degree concept. This approach permits a gradual change of scale value in the classification. Several definitions to the fuzzy numbers are experimented. The results reveal that this approach is a feasible alternative for neural network implementations dealing with quantitative measurements. Examples of using the models for guidance in project management are presented. These include the effect of amount of design completed before construction starts on budget performance, and the effect of amount of time devoted by project manager on schedule performance. The trade-off effect between two key determinants on project outcome can also be studied using the models.
机译:确保令人满意的预算和进度绩效是建设项目的两个主要挑战。在此问题上,预算和进度执行情况的预测模型可以为项目管理资源的适当分配提供帮助。在本研究中,已经开发了两个使用模糊数据进行工程预算和进度绩效的神经网络模型。这些模型分别由八个和五个决定项目成果的关键因素组成。引入组合模糊索引(CFI)方法来表示数据。可以使用模糊数隶属度概念来推导用于输入或输出测量的CFI。这种方法允许在分类中逐渐改变刻度值。实验了模糊数的几种定义。结果表明,该方法对于处理定量测量的神经网络实现方案是可行的。给出了使用模型指导项目管理的示例。其中包括施工开始前完成的设计量对预算绩效的影响,以及项目经理投入的时间对进度绩效的影响。也可以使用模型研究两个关键决定因素之间对项目结果的权衡影响。

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