2024
DOI: 10.4018/979-8-3693-2355-7.ch013
|View full text |Cite
|
Sign up to set email alerts
|

Electricity Production Prediction by Microsoft Azure Machine Learning Service and Python User Blocks

Vladyslav Pliuhin,
Yevgen Tsegelnyk,
Maria Sukhonos
et al.

Abstract: In this chapter, the forecasting of electricity consumption and production is conducted by analyzing indicators from previous years. The problem is addressed using machine learning within Microsoft Azure Machine Learning Studio. The outcome is an independent service integrated into Excel, enabling consumption forecasting for specified dates. The Excel user interface is developed using Visual Basic for Applications. Python was used to create user blocks for modifying input data pools and forming graphical depen… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

0
0
0

Publication Types

Select...

Relationship

0
0

Authors

Journals

citations
Cited by 0 publications
references
References 45 publications
0
0
0
Order By: Relevance

No citations

Set email alert for when this publication receives citations?