基于聚类分析的库存分析系统研究与开发

发布时间：2018-05-17 15:48

本文选题：库存分析 + 数据挖掘　；参考：《沈阳工业大学》2017年硕士论文

【摘要】：随着信息系统的大量应用,海量的数据以及数据处理的需求涌现出来,大数据时代已经到来,数据挖掘技术被越来越多的行业应用。数据挖掘技术融合了统计学和计算机科学等多种学科的一门新兴技术,已被应用到各种需要处理海量数据的场合。聚类分析是数据挖掘中一种方便易用的方法。将聚类分析应用于企业的库存数据分析中,能帮助企业更好的掌握行业市场的动向,从大量纷杂的数据中找到并分析出数据之间的关系,获得有益的信息,帮助企业管理者作出更合理的决策。为此,本文以某企业的库存数据分析为研究对象,从库存数据分析及库存分析系统设计两方面进行研究。本文针对该企业库存数据的特征,从企业的库存分析目标出发,选取二阶聚类算法应用到企业的库存数据分析中,分析库存数据属性将库存物品的周转率、缺货率、资金占用率作为评价库存指标,对库存数据进行分析,分析了企业的库存数量与企业资金的流动,从而使之既能满足客户的需求,又保证库存量不占用大量资金。本文以某汽车零件加工厂为例,完成了对库存分析系统整体的设计与实现。使库存数据的分析管理一体化得以实现,既可以满足企业对库存管理的需求,同时企业的决策者在决策企业运营决定时给予巨大的帮助。为便于企业数据分析网络化实现,系统在Windows2003环境下完成了基于网络的应用系统编程和实现。本文运用SPSS(Statistical Product and Service Solutions统计产品与服务解决方案)对数据进行分析,并在windows开发环境下运用Visual Studio 2013软件进行系统开发,所以采用C#作为开发语言,运用ASP、IIS及网络数据库等技术,设计开发了B/S结构的以数据挖掘技术为核心的库存分析系统。并对系统进行了各个方面的系统测试,结果表明本文所开发的库存分析系统完成了预期设计目标。该系统运行稳定,具有易操作,安全性能高等特点。系统运行测试取得了满意的结果。
[Abstract]:With a large number of applications of information systems, massive data and data processing requirements emerge, the era of big data has come, data mining technology has been more and more industry applications. Data mining technology is a new technology which combines statistics and computer science, and has been applied to various situations where massive data need to be processed. Clustering analysis is a convenient and easy-to-use method in data mining. Applying cluster analysis to enterprise inventory data analysis can help enterprises better grasp the trend of industry market, find and analyze the relationship between data from a large number of complicated data, and obtain useful information. Help managers to make more rational decisions. Therefore, this paper takes the inventory data analysis of a certain enterprise as the research object, carries on the research from the inventory data analysis and the inventory analysis system design. According to the characteristics of the enterprise inventory data, this paper selects the second-order clustering algorithm to apply to the enterprise inventory data analysis from the aim of inventory analysis, and analyzes the inventory data attributes, such as the turnover rate and the stock shortage rate of the inventory items. The capital occupancy rate is used as an evaluation index to analyze the inventory data and analyze the quantity of inventory and the flow of enterprise funds, so that it can not only meet the needs of customers, but also ensure that the stock does not occupy a large amount of capital. Taking an automobile parts processing factory as an example, the whole design and implementation of inventory analysis system are completed in this paper. The integration of analysis and management of inventory data can not only meet the needs of enterprises for inventory management, but also help the decision-makers to make decisions on the operation of enterprises. In order to facilitate the network realization of enterprise data analysis, the application system based on network is programmed and implemented in Windows2003 environment. This paper analyzes the data by using SPSS(Statistical Product and Service Solutions statistical products and services solution, and develops the system with Visual Studio 2013 software under the windows development environment. Therefore, we use C # as the development language, and use the technology of ASP, windows and network database, etc. A B / S structure inventory analysis system with data mining technology as the core is designed and developed. The system is tested in all aspects, and the results show that the inventory analysis system has achieved the expected design goal. The system has the characteristics of stable operation, easy operation and high safety performance. The test results are satisfactory.
【学位授予单位】：沈阳工业大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP393.09;TP311.13

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