Hybrid approach of prediction daily maximum and minimum air temperature for Baghdad City by used artificial neural network and simulated annealing
Other Title(s)
أسلوب الدمج للتنبؤ بدرجات حرارة الهواء الكبرى و الصغرى لمدينة بغداد باستخدام تقنيتي الشبكات العصبية الصناعية مع طريقة محاكاة التلدين
Author
Source
Issue
Vol. 59, Issue 1C (31 Mar. 2018), pp.591-599, 9 p.
Publisher
University of Baghdad College of Science
Publication Date
2018-03-31
Country of Publication
Iraq
No. of Pages
9
Main Subjects
Natural & Life Sciences (Multidisciplinary)
Abstract EN
Temperature predicting is the utilization to forecast the condition of the temperature for an upcoming date for a given area.
Temperature predictions are done by gathering quantitative data in regard to the current state of the atmosphere.
In this study, a proposed hybrid method to predication the daily maximum and minimum air temperature of Baghdad city which combines standard backpropagation with simulated annealing (SA).
Simulated Annealing Algorithm are used for weights optimization for recurrent multi-layer neural network system.
Experimental tests had been implemented using the data of maximum and minimum air temperature for month of July of Baghdad city that got from local records of Iraqi Meteorological Organization and Seismology (IMOS) in period between 2010 to 2016.
The results show that the proposed hybrid method got a high accuracy prediction results that reach nearly from real temperature records of desired year.
American Psychological Association (APA)
Harbah, Hind Salim Ibrahim. 2018. Hybrid approach of prediction daily maximum and minimum air temperature for Baghdad City by used artificial neural network and simulated annealing. Iraqi Journal of Science،Vol. 59, no. 1C, pp.591-599.
https://search.emarefa.net/detail/BIM-837736
Modern Language Association (MLA)
Harbah, Hind Salim Ibrahim. Hybrid approach of prediction daily maximum and minimum air temperature for Baghdad City by used artificial neural network and simulated annealing. Iraqi Journal of Science Vol. 59, no. 1C (2018), pp.591-599.
https://search.emarefa.net/detail/BIM-837736
American Medical Association (AMA)
Harbah, Hind Salim Ibrahim. Hybrid approach of prediction daily maximum and minimum air temperature for Baghdad City by used artificial neural network and simulated annealing. Iraqi Journal of Science. 2018. Vol. 59, no. 1C, pp.591-599.
https://search.emarefa.net/detail/BIM-837736
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 598-599
Record ID
BIM-837736