التفاصيل البيبلوغرافية
| العنوان: |
A New Missing Data Imputation Algorithm Applied to Electrical Data Loggers |
| المؤلفون: |
Concepción Crespo Turrado, Fernando Sánchez Lasheras, José Luis Calvo-Rollé, Andrés José Piñón-Pazos, Francisco Javier de Cos Juez |
| المصدر: |
Sensors, Vol 15, Iss 12, Pp 31069-31082 (2015) |
| بيانات النشر: |
MDPI AG, 2015. |
| سنة النشر: |
2015 |
| المجموعة: |
LCC:Chemical technology |
| مصطلحات موضوعية: |
missing data imputation, multivariate imputation by chained equations (MICE), Multivariate adaptive regression splines (MARS), quality of electric supply, voltage, current, power factor, Chemical technology, TP1-1185 |
| الوصف: |
Nowadays, data collection is a key process in the study of electrical power networks when searching for harmonics and a lack of balance among phases. In this context, the lack of data of any of the main electrical variables (phase-to-neutral voltage, phase-to-phase voltage, and current in each phase and power factor) adversely affects any time series study performed. When this occurs, a data imputation process must be accomplished in order to substitute the data that is missing for estimated values. This paper presents a novel missing data imputation method based on multivariate adaptive regression splines (MARS) and compares it with the well-known technique called multivariate imputation by chained equations (MICE). The results obtained demonstrate how the proposed method outperforms the MICE algorithm. |
| نوع الوثيقة: |
article |
| وصف الملف: |
electronic resource |
| اللغة: |
English |
| تدمد: |
1424-8220 |
| Relation: |
http://www.mdpi.com/1424-8220/15/12/29842; https://doaj.org/toc/1424-8220 |
| DOI: |
10.3390/s151229842 |
| URL الوصول: |
https://doaj.org/article/2ce7742aeed943069d878694ddde714f |
| رقم الانضمام: |
edsdoj.2ce7742aeed943069d878694ddde714f |
| قاعدة البيانات: |
Directory of Open Access Journals |
Full Text Finder