Real-Time Data Assimilation for Improving Linear Municipal Solid Waste Prediction Model: A Case Study in Seattle
文献类型：期刊论文
| 作者 | Song, Jingwei1; He, Jiaying1; Zhen, Jing1 |
| 刊名 | JOURNAL OF ENERGY ENGINEERING
 |
| 出版日期 | 2015 |
| 卷号 | 141期号:4页码:735-744 |
| 关键词 | Municipal solid waste Data assimilation Kalman filter Seasonal autoregressive integrated moving average (SARIMA) Time series forecast |
| 通讯作者 | Song, JW (reprint author), Chinese Acad Sci, Inst Remote Sensing & Digital Earth, Key Lab Digital Earth Sci, 9 Dengzhuang South Rd, Beijing 100094, Peoples R China. |
| 英文摘要 | A commonly used data assimilation (DA) algorithm, Kalman filter, is integrated with the seasonal autoregressive integrated moving average (SARIMA) model to make a one-step forecast of monthly municipal solid waste (MSW) generation in Seattle. The DA solves the problem that parameters of the forecasting model need to be updated in every forecasting process. The performances of prediction models are compared using mean absolute percentage error (MAPE), root-mean-square-error (RMSE), and 95% confidence interval. The MAPE of the SARIMA model with DA is 0.0422, whereas the MAPE of the SARIMA without DA is 0.0914. A 95% confidence interval of SARIMA without DA keeps increasing, whereas SARIMA with DA remains constant, which means DA raises the stability of SARIMA as time progresses. Results show that DA enables the same MSW prediction model with more accurate and more robust forecast results. The SARIMA parameter updating cycle can be prolonged, which saves time and effort. (C) 2014 American Society of Civil Engineers. |
| 研究领域[WOS] | Energy & Fuels ; Engineering, Civil |
| 收录类别 | SCI ; EI |
| 语种 | 英语 |
| WOS记录号 | WOS:000365120400006 |
| 源URL | [http://ir.ceode.ac.cn/handle/183411/38058]  |
| 专题 | 遥感与数字地球研究所_SCI/EI期刊论文_期刊论文 |
| 作者单位 | 1.[Song, Jingwei 2.Zhen, Jing] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, Key Lab Digital Earth Sci, Beijing 100094, Peoples R China 3.[Song, Jingwei 4.Zhen, Jing] Chinese Acad Sci, Grad Sch, Beijing 100049, Peoples R China 5.[He, Jiaying] Univ Georgia, Dept Geog, Ctr Geospatial Res, Athens, GA 30602 USA |
| 推荐引用方式 GB/T 7714 | Song, Jingwei,He, Jiaying,Zhen, Jing. Real-Time Data Assimilation for Improving Linear Municipal Solid Waste Prediction Model: A Case Study in Seattle[J]. JOURNAL OF ENERGY ENGINEERING,2015,141(4):735-744. |
| APA | Song, Jingwei,He, Jiaying,&Zhen, Jing.(2015).Real-Time Data Assimilation for Improving Linear Municipal Solid Waste Prediction Model: A Case Study in Seattle.JOURNAL OF ENERGY ENGINEERING,141(4),735-744. |
| MLA | Song, Jingwei,et al."Real-Time Data Assimilation for Improving Linear Municipal Solid Waste Prediction Model: A Case Study in Seattle".JOURNAL OF ENERGY ENGINEERING 141.4(2015):735-744. |
入库方式： OAI收割
来源：遥感与数字地球研究所
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