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Analysis on the Strategy for Construction Quality Optimization Management of Municipal Road Engineering Based on Fast Mining Algorithm for Large Cloud Data

机译:基于大云数据快速挖掘算法的市政道路工程施工质量优化管理策略分析

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In view of the insufficient in the existing researches that the non-linearity of subcontracting resource system for the municipal road engineering construction is ignored, combined with the theory of road construction quality optimization management in the context of cloud data, a kind of strategy for construction quality optimization management of municipal road engineering based on fast mining algorithm for large cloud data (referred to as FMALCD for short) is put forward to achieve the effective analysis on the construction quality optimization management of the municipal road engineering. Firstly, after the identification of the conditions under the dynamic constraints of the municipal road engineering construction, the serial number of the first construction node is calculated. Reordering is carried out to meet the optimization characteristics of the construction quality optimization management. In the FMALCD, the nonlinear characteristics of a kind of fast mining for the cloud data is combined in the application to further optimize the issue of the municipal road engineering construction quality optimization management. In addition, analysis is carried out on the performance of the algorithm through simulation experiment. The analysis is conducted mainly from the perspective of effectiveness, relative advantages and so on.
机译:鉴于现有研究不足,忽略了市政道路工程建设分包资源系统的非线性问题,结合云数据背景下的道路建设质量优化管理理论,提出了一种建设策略提出了基于大数据快速挖掘算法的市政道路工程质量优化管理(简称FMALCD),以实现对市政道路工程施工质量优化管理的有效分析。首先,在确定了市政道路工程施工动态约束条件后,计算出第一个施工节点的序列号。进行重新排序以满足建筑质量优化管理的优化特征。在FMALCD中,结合了一种对云数据的快速挖掘的非线性特性,在应用中进一步优化了市政道路工程施工质量优化管理的问题。另外,通过仿真实验对算法的性能进行了分析。主要从有效性,相对优势等角度进行分析。

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