Research on prediction method of api based on the enhanced moving average method

Author

Zhenghai Zhang ; Zhifang Jiang ; Xiangxu Meng ; Shenghui Cheng ; Wei Sun

Author_Institution

Sch. of Comput. Sci. & Technol., Shandong Univ., Jinan, China

fYear

2012

fDate

19-20 May 2012

Firstpage

2388

Lastpage

2392

Abstract

According to the ambient air quality monitoring data of a city in recent ten years, an Air Pollution Index (API) prediction method using statistical prediction methods has been studied. An integrated prediction model using the average of the longer and shorter period moving average value has been proposed. The experiment result shows that the prediction accuracy of this model is better than that of the conventional moving average statistical prediction method for different periods of the city´s API.

Keywords

air pollution; moving average processes; statistical analysis; API prediction method; air pollution index predition method; ambient air quality monitoring data; enhanced moving average method; integrated prediction model; longer period moving average value; moving average statistical prediction method; prediction accuracy; shorter period moving average value; statistical prediction methods; Accuracy; Air pollution; Cities and towns; Educational institutions; Error analysis; Monitoring; Time series analysis; API; Moving Average; Prediction; Statistics; Time Series;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems and Informatics (ICSAI), 2012 International Conference on

Conference_Location

Yantai

Print_ISBN

978-1-4673-0198-5

Type

conf

DOI

10.1109/ICSAI.2012.6223534

Filename

6223534