使用模糊OLAP多维数据集灵活管理基本构建任务

Nicolás Marín Ruíz, M. Martínez-Rojas, C. M. Férnandez, J. M. Soto-Hidalgo, J. Rubio-Romero, María Amparo Vila Miranda
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引用次数: 2

摘要

近几十年来,建筑行业有了显著的发展,与此同时,任何建筑项目中产生和交换的数据量也在大幅增加。这些数据需要管理,以便在安全的项目环境下,在质量、成本和进度方面完成一个成功的项目,同时适当地组织许多施工文件。然而,这些数据的来源是非常多样化的,主要是由于行业的特点。此外,由于建筑项目中涉及的许多因素的不精确性,这些数据受到不确定性、复杂性和多样性的影响。因此,建设项目数据与大型、不规则和分散的数据集相关联。本章的目的是介绍一种基于模糊多维模型和在线分析处理(OLAP)操作的方法,以管理施工数据并支持基于以往经验的决策过程。一方面,该提案允许将数据集成到一个公共存储库中,用户可以在整个项目的生命周期中访问该存储库。另一方面,它允许建立更灵活的结构来表示建设项目管理领域中主要任务的数据。这种模糊框架的结合允许管理建筑数据中的不精确,并为用户提供简单直观的访问,以便他们可以做出更可靠的决策。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Flexible Management of Essential Construction Tasks Using Fuzzy OLAP Cubes
Abstract The construction sector has significantly evolved in recent decades, in parallel with a huge increase in the amount of data generated and exchanged in any construction project. These data need to be managed in order to complete a successful project in terms of quality, cost and schedule in the the context of a safe project environment while appropriately organising many construction documents. However, the origin of these data is very diverse, mainly due to the sector’s characteristics. Moreover, these data are affected by uncertainty, complexity and diversity due to the imprecise nature of the many factors involved in construction projects. As a result, construction project data are associated with large, irregular and scattered datasets. The objective of this chapter is to introduce an approach based on a fuzzy multi-dimensional model and on line analytical processing (OLAP) operations in order to manage construction data and support the decision-making process based on previous experiences. On one hand, the proposal allows for the integration of data in a common repository which is accessible to users along the whole project’s life cycle. On the other hand, it allows for the establishment of more flexible structures for representing the data of the main tasks in the construction project management domain. The incorporation of this fuzzy framework allows for the management of imprecision in construction data and provides easy and intuitive access to users so that they can make more reliable decisions.
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