A Time-Series Water Level Forecasting Model Based on Imputation and Variable Selection Method
المؤلفون المشاركون
Cheng, Ching-Hsue
Yang, Jun-He
Chan, Chia-Pan
المصدر
Computational Intelligence and Neuroscience
العدد
المجلد 2017، العدد 2017 (31 ديسمبر/كانون الأول 2017)، ص ص. 1-11، 11ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2017-11-09
دولة النشر
مصر
عدد الصفحات
11
التخصصات الرئيسية
الملخص EN
Reservoirs are important for households and impact the national economy.
This paper proposed a time-series forecasting model based on estimating a missing value followed by variable selection to forecast the reservoir’s water level.
This study collected data from the Taiwan Shimen Reservoir as well as daily atmospheric data from 2008 to 2015.
The two datasets are concatenated into an integrated dataset based on ordering of the data as a research dataset.
The proposed time-series forecasting model summarily has three foci.
First, this study uses five imputation methods to directly delete the missing value.
Second, we identified the key variable via factor analysis and then deleted the unimportant variables sequentially via the variable selection method.
Finally, the proposed model uses a Random Forest to build the forecasting model of the reservoir’s water level.
This was done to compare with the listing method under the forecasting error.
These experimental results indicate that the Random Forest forecasting model when applied to variable selection with full variables has better forecasting performance than the listing model.
In addition, this experiment shows that the proposed variable selection can help determine five forecast methods used here to improve the forecasting capability.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Yang, Jun-He& Cheng, Ching-Hsue& Chan, Chia-Pan. 2017. A Time-Series Water Level Forecasting Model Based on Imputation and Variable Selection Method. Computational Intelligence and Neuroscience،Vol. 2017, no. 2017, pp.1-11.
https://search.emarefa.net/detail/BIM-1141197
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Yang, Jun-He…[et al.]. A Time-Series Water Level Forecasting Model Based on Imputation and Variable Selection Method. Computational Intelligence and Neuroscience No. 2017 (2017), pp.1-11.
https://search.emarefa.net/detail/BIM-1141197
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Yang, Jun-He& Cheng, Ching-Hsue& Chan, Chia-Pan. A Time-Series Water Level Forecasting Model Based on Imputation and Variable Selection Method. Computational Intelligence and Neuroscience. 2017. Vol. 2017, no. 2017, pp.1-11.
https://search.emarefa.net/detail/BIM-1141197
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1141197
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر