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Imputation as Service Using Support Vector Regression: Application to a Photovoltaic System in Algeria

Domain:

environment and energy

Record type:

paper
Creator:
SedKadAbd
Editor:
Lab
Publisher:
CCSD
Host:avatar
International audience This paper aims to test the most common imputation methods' effectiveness and choose the most appropriate methods for our data model. In the experimental study, we applied imputation to missing data using the imputation methods: fFill, bFfil, Drop, and Support Vector Regression (SVR). An easy and practical means of comparison is used to evaluate the effectiveness of imputation methods. Therefore, the classification quality criterion is used, and column reference graphs are used because they have a statistically significant relationship. The SVR imputation method was very reliable, and it helped us make a reasonable classification.

Visit

hal.science

Tags

Missing valueImputationClassificationPhotovoltaic systemMeteorological data[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI][SPI.NRJ]Engineering Sciences [physics]/Electric power

Licenses

info:eu-repo/semantics/OpenAccess

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