We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
基于 ARIMA 模型的大坝安全监测数据分析与预测.
- Authors
解建仓; 王 玥; 雷社平; 李 想; 吕正祥
- Abstract
Dam safely monitoring data is lime series data with trend and seasonal characteristics. In order to analyze and predict it accurately, AR1MA model could he applied to deal with this unstable time series. In details, firstly, it got stable time series by difference. Secondly, it identified the model by AFC and PAFC and got some trial models. Thirdly, it estimated the parameters of these trial models and confirmed the final model according to Bayesian Information Criterion. Finally, it filled and predicted the monitoring data with the final model. Taking Lij iaxia dam as an example, it built the model based on above process and compared the model data with monitoring data. The result shows that AH IMA is accurate when analyzing dam safely monitoring data and predicting it in a short-term. In short, AR1MA is a feasibility study.
- Publication
Yellow River, 2018, Vol 40, Issue 10, p131
- ISSN
1000-1379
- Publication type
Article
- DOI
10.3969/j.issn.1000-1379.2018.10.029