摘要
目前我国在科技管理上大多采用的是被动的行政管理方式,领导层的决策缺乏客观的科学依据。为了提高科技管理水平,实现科学的量化管理,以某商业银行信息中心为例,利用生产系统运行记录中的数据,运用时间序列分析理论,通过对故障次数、交易量等生产数据进行平稳性检验、正态性检验,数据分析表明可以进行建模预测。同时在进一步进行数据的相关性分析的基础上,确定建模类型,试图根据数据的内在特性,运用一定的科学手段去挖掘,最终建立科学的事件预测机制。
At present, the style of administration management is passive; and the decisions made by leaders lack an objective scientific foundation in our country. In order to improve the level of management and implement scientific measurable management, this paper takes an information center of a business bank as an example, makes use of the data generated by product system with the application of the time series analysis theory, and analyzes the data of trouble count and trade count for a stationarity test and a normality test. The data analysis makes it clear that the model can be made to forecast the data. On the foundation of the deeper analysis of the data correlation, this type of model can be confirmed; and the scientific forecast system can be eventually set up by the scientific means according to the inherent features of the data.
出处
《北京印刷学院学报》
2007年第6期48-51,共4页
Journal of Beijing Institute of Graphic Communication
关键词
金融数据序列
检验
建模
预测
financial data series
validation
modeling
forecast
