基于云计算的股票数据分析研究与实现

发布时间：2019-01-17 12:49

【摘要】：云计算作为一种新兴的计算模式一经提出便得到工业界、学术界的广泛关注，它能够为用户提供灵活的、按需分配的、廉价的服务。云计算具有变革互联网服务的潜在能力。各个国家都在积极建设面向社会开放、功能齐全的云计算公共服务平台。随着世界经济和股票市场的发展，越来越多的人将股票投资作为一种理财方式。在我国，股票证券交易不过十几年时间，但是发展却非常快。然而，面对海量的股票交易数据，人们往往不能很好利用这些数据去为自己的决策提供支持，而是通过决策者的直观感受来做出决定，没有有效的工具和技术来从海量的数据中提取有价值的信息。国内市场也有不少的股票分析软件，但都大同小异，在大数据的环境下没有帮助股民进行智能分析的能力，对股票的价格走向的预测有时完全不准确。因此建设基于云计算的智能股票分析系统具有重大的意义,研发一个面向大数据的智能股票分析云平台面向社会服务是一个急需解决的问题。本课题主要研究基于云计算平台的并行计算对股票交易数据进行实时分析和预测，与此同时对云平台的计算资源进行远程管控。本论文的主要研究内容如下：首先,建立了云平台门户系统,该系统面向各种用户形成各种子系统的统一门户，实现了对云计算环境下的资源管控。其次，建立了基于云计算的数据安全管理系统，该系统解决了用户数据的存储、传输的加解密问题保证了数据的安全性，实现了对云计算环境下的安全管控。最后，建立了基于云计算的智能股票分析系统，对神经网络、主成分分析等数据挖掘算法进行了相应的研究，设计实现了基于BP神经网络的股票价格预测分析方法。该系统通过和集群进行实时通信，得到详细股票数据情况，并进行图形化展示，这充分利用了云平台的计算性能。该课题研究与实现了云计算环境下的股票数据分析系统，满足了对股票等大数据处理和分析的需要，所建立的财务分析、智能选股、量价分析、信息检索等模型对股票投资有一定的指导和参考价值。这对于企业和个人都具有十分重要的意义。
[Abstract]:Cloud computing as a new computing model has been widely concerned by industry and academia. It can provide users with flexible, on-demand, low-cost services. Cloud computing has the potential to transform Internet services. All countries are actively building open and fully functional cloud computing public service platform. With the development of world economy and stock market, more and more people take stock investment as a way of financing. In our country, stock and securities trading only a dozen years, but the development is very fast. However, in the face of massive stock trading data, people often can not make good use of these data to provide support for their own decisions, but through the intuitive feelings of decision makers to make decisions. There are no effective tools and techniques to extract valuable information from vast amounts of data. The domestic market also has many stock analysis software, but all are similar, in big data's environment does not have the ability to help the stock owner to carry on the intelligent analysis, the forecast to the stock price trend sometimes is completely inaccurate. Therefore, it is of great significance to build an intelligent stock analysis system based on cloud computing. It is an urgent problem to develop an intelligent stock analysis cloud platform oriented to social service for big data. This paper mainly studies the real-time analysis and prediction of stock trading data based on parallel computing based on cloud computing platform, and at the same time, remotely controls the computing resources of cloud platform. The main contents of this thesis are as follows: firstly, a cloud platform portal system is established, which forms a unified portal for all kinds of users and realizes resource management and control in cloud computing environment. Secondly, the data security management system based on cloud computing is established. The system solves the storage of user data, the problem of encryption and decryption of transmission ensures the security of data, and realizes the security control of cloud computing environment. Finally, an intelligent stock analysis system based on cloud computing is established, and the corresponding data mining algorithms such as neural network and principal component analysis are studied, and the stock price prediction and analysis method based on BP neural network is designed and implemented. Through real-time communication with the cluster, the system can get detailed stock data and display it graphically, which makes full use of the computing performance of the cloud platform. This research and implementation of cloud computing environment of stock data analysis system, meet the need to deal with and analyze the stock big data, the established financial analysis, intelligent stock selection, volume and price analysis, The information retrieval model has certain guidance and reference value for stock investment. This is of great significance to both enterprises and individuals.
【学位授予单位】：湖南大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TP3;F832.51

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