J4 ›› 2015, Vol. 14 ›› Issue (6): 13-17.

• 数学与计算机科学 • 上一篇    下一篇

生态环境数据预测方法研究

  

  1. 大理学院数学与计算机学院,云南大理 671003
  • 收稿日期:2014-08-17 出版日期:2015-06-15 发布日期:2015-06-15
  • 作者简介:罗桂兰,副教授,博士,主要从事嵌入式物联网技术研究.
  • 基金资助:

    大理学院博士启动基金资助项目(KYBS201015);云南省创新训练项目(2012S- CXCY-6);大理学院创新训练
    项目(X-CXCY-2014-9)

Research on Prediction Method of Ecological Environmental Data

  1. College of Mathematics and Computer, Dali University, Dali, Yunnan 671003, China
  • Received:2014-08-17 Online:2015-06-15 Published:2015-06-15

摘要:

大规模生态环境数据的处理和统计分析为环境保护和预测提供重要依据,其分析和预测方法成为数据处理的研究重
点。在对海量生态环境数据的分类整理和综合处理基础上,基于时间序列的指数平滑法建立了一种动态二次指数生态环境数
据预测模型。该模型针对生态环境的实时变化特征,利用二次指数平滑方法实现了静态参数的动态优化处理。以云南大理生
态环境数据为样本,通过实验仿真测试和模型分析,结果验证了该模型的适用性和准确性。

关键词: 生态环境, 指数平滑法, 动态预测

Abstract:

Large scale ecological environmental data processing and statistical analysis results can provide important bases for
environmental protection and prediction, the analysis and prediction method become the research emphases in data processing. In this
paper, based on the classification and comprehensive data processing of magnanimous ecological environment data, a prediction model
of ecological environment data is established based on dynamic and two exponential smoothing method of time series. Aiming at the
real- time variation of ecological environment, the dynamic optimization process of static parameters is realized by using two
exponential smoothing methods. Taking the ecological environment data of Dali, Yunnan as the sample, through the simulation test and
the model analysis, its results verify the applicability and accuracy of the model.

Key words: ecological environment, exponential smoothing method, dynamic prediction

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