基于大数据挖掘的仓库质量自动评分模型构建

Construction of automatic scoring model for warehouse quality based on big data mining

近几年来随着我国仓库的规模不断扩大,仓库建设工程技术的不断升级,但仓库质量保障体系却显得有点跟不上发展的进程,质量评估水平较为落后。因此基于大数据挖掘对仓库质量进行评分模型构建。首先结合数据挖掘算法对仓库结构安全参数和承载负荷等数据进行计算,结合安全参数算法及仓库安全性检测评估指标对仓库质量自动评分系统进行建模,采用层次分析法对仓库进行综合评估。最后通过实验检测证实,基于大数据挖掘对仓库质量进行评分模型构建可有效地提高仓库建筑评估水平。

In recent years,with the continuous expansion of the scale of our country’s warehouses and the continuous upgrading of warehouse construction technology,the warehouse quality assurance system seems to be a little behind the development process and the quality evaluation level is relatively backward.Therefore,a scoring model for warehouse quality is constructed based on big data mining.Firstly,data mining algorithm is used to calculate data such as warehouse structure safety parameters and load bearing capacity,and safety parameter algorithm and warehouse safety detection and evaluation index are used to model the warehouse quality automatic scoring system.Analytic hierarchy process is used to comprehensively evaluate the warehouse.Finally,the experiment proves that the evaluation level of warehouse buildings can be effectively improved by building a scoring model for warehouse quality based on big data mining.