NDLI: A environment data behavior analysis algorithm based on dynamic exponential smoothing method

Content Provider	IEEE Xplore Digital Library
Author	Guilan Luo Libo Feng
Copyright Year	2014
Description	Author affiliation: Inst. of Math. & Comput., Dali Univ., Dali, China (Guilan Luo; Libo Feng)
Abstract	Along with the global climate warming, the ecological environment of the earth changes sharply. In order to prevent the worsening environment and protect the benign development trend, dynamic environment monitoring and real-time data analysis becomes necessary. Large scale ecological environmental data processing and statistical analysis results can provide an important basis for environmental protection and prediction, the analysis and prediction method becomes the research emphasis in data processing. In this paper, based on the classification and comprehensive data processing of magnanimous ecological environment data, a ecological environment behavior analysis algorithm based on exponential smoothing method of time series is presented. Aiming at the real-time variation of ecological environment, the dynamic optimization process of static parameters is realized by using two exponential smoothing model. Through simulation test and the performance analysis of algorithm, such as correlation and independence, its results verify the applicability and accuracy of algorithm.
Starting Page	838
Ending Page	842
File Size	337962
Page Count	5
File Format	PDF
e-ISBN	9781479958382
DOI	10.1109/BMEI.2014.7002888
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-10-14
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	exponential smoothing Smoothing methods Correlation Biological system modeling Heuristic algorithms Humidity behavior analysis Predictive models Market research time series dynamic optimization ecological environment
Content Type	Text
Resource Type	Article

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