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
Precipitation Forecasting Assessment via Nonlinear Autoregressive Neural Network and Vector Autoregressive Models
Date
2013-06-28
Author
Aslan, Sipan
İyigün, Cem
Yozgatlıgil, Ceylan
Batmaz, İnci
Metadata
Show full item record
Item Usage Stats
123
views
0
downloads
Cite This
URI
https://hdl.handle.net/11511/73444
Collections
Unverified, Conference / Seminar
Suggestions
OpenMETU
Core
Precipitation prediction by hidden markov models
Batmaz, İnci; Yazıcı, Ceyda; Yozgatlıgil, Ceylan (null; 2014-06-18)
Precipitation Modeling by Polyhedral RCMARS and Comparison with MARS and CMARS
Ozmen, Ayse; Batmaz, İnci; Weber, Gerhard-Wilhelm (2014-10-01)
Climate change is becoming an ever important issue due to the possibility that it may result in extreme weather events such as floods or droughts. Consequently, precipitation forecasting has similarly gained in significance as it is a useful tool in meeting the increasing need for the efficient management of water resources as well as in preventing disasters before they happen. In the literature, there are various statistical and computational methods used for this purpose, including linear and nonlinear re...
Drought Forecasting with Time Series and Machine Learning Approaches
Evkaya, Ömer Ozan; Yozgatlıgil, Ceylan; Kestel, Sevtap Ayşe (null; 2017-12-08)
As a main reason of undesired agricultural, economic and environmental damages, drought is one of the most important stochastic natural hazard having certain features. In order to manage the impacts of drought, more than 100 drought indices have been proposed for both monitoring and forecasting purposes [1], [3]. For different types of droughts, these indices have been used to understand the effects of dry periods including meteorological, agricultural and hydrological droughts in many distinct locations. I...
Rainfall runoff modelling with green-ampt infiltration process.
San, Ovul; Sevük, Süha; Department of Civil Engineering (1993)
Rainfall network design approaches and applications.
Balkan, Guven; Department of Civil Engineering (1979)
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
S. Aslan, C. İyigün, C. Yozgatlıgil, and İ. Batmaz, “Precipitation Forecasting Assessment via Nonlinear Autoregressive Neural Network and Vector Autoregressive Models,” 2013, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/73444.