[1]张晓杰,张希良.时间序列分析模型在山东省粮食总产量预测中的应用[J].水土保持研究,2007,14(03):309-311.
ZHANG Xiao-jie,ZHANG Xi-liang.Application of Time Series Analysis Model on Total Corn Yield of Shandong Province[J].Research of Soil and Water Conservation,2007,14(03):309-311.
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《水土保持研究》[ISSN:1005-3409/CN:61-1272/P]
卷:
14
期数:
2007年03期
页码:
309-311
栏目:
出版日期:
1900-01-01
- Title:
-
Application of Time Series Analysis Model on Total Corn Yield of Shandong Province
- 作者:
-
张晓杰1, 张希良2
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1. 鲁东大学地理与资源管理学院, 烟台, 264025;
2. 莒县四中, 日照, 276500
- Author(s):
-
ZHANG Xiao-jie1, ZHANG Xi-liang2
-
1. Geography and Resources Management College of Ludong University, Yantai, Shandong 264025, China;
2. No.4 High Middle School of Juxian, Rizhao 276500, China
-
- 关键词:
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传统时间序列分析模型; ARIMA模型; 拟合精度; 预测
- Keywords:
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classical time series analysis model; ARIMA; fitted precision; prediction
- 分类号:
-
F307
- 摘要:
-
对比传统时间序列分析模型(线性回归、二次滑动平均、一次平滑、二次指数平滑和三次指数平滑等)与ARIMA模型在山东省粮食总产量中的拟合精度,并应用ARIMA(2,1,12)模型预测了未来年内山东省粮食总产量.结果表明,在山东省粮食总产量拟合中,ARIMA(2,1,12)模型得到的粮食总产量拟合值与观测值的相对误差处于±10%和±5%范围内的分别为7.%和5.%,回归方程的决定系数为0.959,优于传统时间序列分析模型;利用ARIMA(2,1,12)模型预测未来年内山东省粮食总产量,粮食总产量有逐年上升的趋势,且增长率逐年上升.
- Abstract:
-
The classical time series analysis model(linear regression,two step moving average,one step smoothing,two step EXSMOOTH,three step EXSMOOTH,etc.) and the ARIMA model were compared to predict total corn yield,and ARIMA(2,1,12) model was applied to predict the total corn yield in future 3 years.Results showed that the ARIMA(2,1,12) model was better than the classical time series analysis model in total corn yield of Shandong Province.The determine coefficient of regressive equation was 0.959 and the relative error between fitted value and measured value among 73.333% and 53.333% were ±10% and ±5%,respectively.The total corn yield and the increasing ratio ascended year by year in future 3 years with predicting model of ARIMA(2,1,12) applied.
参考文献/References:
[1] 石美娟.ARIMA模型在上海市全社会固定资产投资预测中的应用[J].数理统计与管理, 2005, 24(1):69-74.
[2] G P E Box, G M Jenkins.Time Series Analysis:Forecasting and Control[M].San Francisco:San Francisco Press, 1978.
[3] 高雷, 张蕾.基于市场周转率的股票市场收益预测[J].经济经纬, 2004,(6):127-128.
[4] 李勇, 等.基于乘积ARIMA模型的产品不确定性需求预测[J].系统工程与电子技术, 2005, 27(1):60-62.
[5] 韦丽琴, 等.ARIMA模型在交通事故预测中的应用[J].包头医学院学报, 2004, 20(4):287-288.
[6] 史其信, 郑为中, 等.道路网短期交通流预测方法比较[J].交通运输工程学报, 2004, 4(4):68-71.
[7] 张莹, 等.露天矿一类时间参数的ARIMA 模型预测[J].矿冶, 2004, 13(4):80-82.
更新日期/Last Update:
1900-01-01