基于云计算的室内建筑工程质量验收监督方法

IF 2.1 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Journal of Intelligent Systems Pub Date : 2022-01-01 DOI:10.1515/jisys-2022-0056
Jian Zhang
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引用次数: 0

摘要

建筑业作为中国经济的重要组成部分,对经济的贡献巨大,在中国经济发展中发挥着重要作用。因此,对建设工程质量验收监督方法具有一定的研究意义。本文以深圳S工程为例,结合云计算,探讨室内建筑工程的质量验收和监理方法。在技术部分的介绍中,本文首先简要介绍了云计算的定义,然后介绍了粒子群算法和传统遗传算法在云计算任务调度中的应用方法。将该算法引入室内建筑工程的质量验收中,以获得质量最优、效率最高的验收监督方法。本文的实验部分以S项目为研究对象,以居民对项目的满意度为实验目的。最后通过统计分析得出,居民对S项目的满意度达到70%以上。
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Supervision method of indoor construction engineering quality acceptance based on cloud computing
Abstract As an important part of Chinese economy, the construction industry has a great contribution to the economy, and plays an important role in the Chinese economic development. Therefore, it has certain research significance for the quality acceptance supervision method of construction engineering. This article takes Shenzhen S project as an example, combined with cloud computing, discusses the quality acceptance and supervision methods of indoor construction projects. In the introduction to the technical part, this article first briefly introduces the definition of cloud computing and then introduces the particle swarm algorithm and traditional genetic algorithm in the cloud computing task scheduling method. The algorithm is introduced into the quality acceptance of indoor construction projects to obtain the quality, most efficient method for acceptance supervision. The experimental part of this article takes S project as the research object and the residents’ satisfaction with the project as the experimental purpose. Finally, through statistical analysis, it is concluded that the residents’ satisfaction with S project reaches more than 70%.
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来源期刊
Journal of Intelligent Systems
Journal of Intelligent Systems COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-
CiteScore
5.90
自引率
3.30%
发文量
77
审稿时长
51 weeks
期刊介绍: The Journal of Intelligent Systems aims to provide research and review papers, as well as Brief Communications at an interdisciplinary level, with the field of intelligent systems providing the focal point. This field includes areas like artificial intelligence, models and computational theories of human cognition, perception and motivation; brain models, artificial neural nets and neural computing. It covers contributions from the social, human and computer sciences to the analysis and application of information technology.
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