Show/Hide Menu
Hide/Show Apps
anonymousUser
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Açık Bilim Politikası
Açık Bilim Politikası
Frequently Asked Questions
Frequently Asked Questions
Browse
Browse
By Issue Date
By Issue Date
Authors
Authors
Titles
Titles
Subjects
Subjects
Communities & Collections
Communities & Collections
Using artificial neural network (ANN) techniques for solar irradiation predictions
Download
index.pdf
Date
2019
Author
Akbaba, Erol Can
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
3
views
0
downloads
Estimation of solar energy is a task with many benefits to a diverse group of people. This purpose is pursued with many different methodologies. Artificial Neural Networks (ANNs) are the novel methods of choice in the last decade. We compare the classical solar irradiation estimation methods with different ANN schemes including different inputs, data amount and estimation target. Our analyses show that the use of ANN to predict solar irradiation reaching the Earth’s surface gives similar results with that of the classical regression approaches. The small difference between these two approaches lies within the instrumentation accuracy of the measuring devices.
Subject Keywords
Solar energy.
,
Keywords: Solar energy
,
estimation
,
machine learning
,
deep learning
,
artificial neural network.
URI
http://etd.lib.metu.edu.tr/upload/12624006/index.pdf
https://hdl.handle.net/11511/44708
Collections
Graduate School of Natural and Applied Sciences, Thesis