Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Hibrit Yenilenebilir Enerji Sistemleri için Boyutlandırma Modellerinin Karşılaştırması
Date
2020-11-01
Author
Al-ghussain, Loiy
Taylan, Onur
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
264
views
0
downloads
Cite This
URI
http://www.elsevier.com/books/hybrid-energy-system-models/berrada/978-0-12-821403-9
https://hdl.handle.net/11511/89398
Relation
Hibrit Enerji Sistem Modelleri
Collections
Department of Mechanical Engineering, Book / Book chapter
Suggestions
OpenMETU
Core
Application of a Hybrid Machine Learning model on short term electricty demand prediction
Assar, Ahmed Khaled Ahmed Farouk; Fahrioğlu, Murat; Sustainable Environment and Energy Systems (2022-2)
Electricity demand forecasting is an important procedure in the electricity market and plays a great role in assuring a sustainable and efficient operation chain. By accurately forecasting the demand, one can see a considerable reduction in production costs as well as saving energy resources. Therefore, optimizing the demand forecasting techniques became an inseparable goal of power economics, leading to the introduction of machine learning to this sector that proved to be superior to other pre-defined alte...
Modelling and transient analysis of a hybrid liquid desiccant cooling system
Karshenass, Arash; Yamalı, Cemal; Baker, Derek Keıth; Department of Mechanical Engineering (2014)
Desiccant Cooling Systems (DCS) are considered as an alternative method for conventional vapor compression cooling systems (VCCS) or at least a complimentary component to them. In conventional VCCS inlet air is cooled down to blow its dew point for dehumidification and then is reheated again to obtain air flow with desired temperature and humidity, and consequently inefficient consumption of energy. In DCS, dehumidification of air is done by utilizing of desiccant material to get desirable humidity and then...
Performance of hybrid machine learning algorithms on financial time series data
Sayın, Merve Gözde; Yozgatlıgil, Ceylan; Uğur, Ömür; Department of Financial Mathematics (2021-2-5)
Estimating stock indices that reflect the market has been an essential issue for a long time. Although various models have been studied in this direction, historically, statistical methods and then various machine learning methods have to introduced artificial intelligence into our lives. Related literature shows that neural networks and treebased models are mostly used. In this direction, in this thesis, four different models are examined. The first one is the most preferred neural network method for finan...
Hibrit hedef kestirim algoritması tasarımı
Kale, Suzan; Kutay, Ali Türker (2014-07-01)
Hybrid excited synchronous generator design and comparison of direct drive wind turbines
Akgemci, Aysel; Keysan, Ozan; Department of Electrical and Electronics Engineering (2019)
Various types of electrical generators are used in wind turbines and there is not an agreement on the best generator type. Although, high speed Doubly Fed Induction Generators (DFIGs) are still the most common generator topology utilized in wind turbine systems, there is a trends toward direct-drive Permanent Magnet Synchronous Generators (PMSGs), as they are more efficient and reliable. However, permanent magnets (PMs) induce uncontrollable voltage due to the fixed flux resulting from PM excitation. Conven...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
L. Al-ghussain and O. Taylan,
Hibrit Yenilenebilir Enerji Sistemleri için Boyutlandırma Modellerinin Karşılaştırması
. 2020.