Estimating Daily Maximum Temperatures Using Artificial Networks (Case study: Kerman)
Subject Areas : Climatology
Shokoufeh Omidi ghaleh mohammadi
1
(
Yazd University
Department of Sceiences Humanities
Faculty of Geography
)
Ahmad Mazidi
2
(
Yazd University
Department of Sceiences Humanities
Faculty of Geography
)
Sodabh Karemi
3
(
Yazd University
Department of Sceiences Humanities
Faculty of Geography
)
Najmeh Hassani sadi
4
(
Yazd University
Department of Sceiences Humanities
Faculty of Geography
)
Mahboobeh Omidi ghaleh mohammadi
5
(
The Dissertation of M.Sc. in Department Of Climatology (Field of Applied Climatology)،The University of Sistan & Baluchestan
Graduate School
)
hassan kharajpor
6
(
The Dissertation of M.Sc. in Department Of Climatology ،Field of Applied Climatology، Kharazmi University of Tehran
)
Keywords: daily maximum temperatures, Kerman, Artificial Neural Networks, Estimation,
Abstract :
Considering the capability of the artificial neural networks in simulating sophisticated processes, it is being used in estimation and computation of climatic parameters. The goal of this research is to estimate the daily maximum temperature in Kerman province. To this aim, daily climatic parameters as input to the neural networks and daily maximum temperature as the output during a statistical period of 24 years (1989-2013) were used, the findings revealed that the output of the multi-layer perceptron neural network, considering the error amount and correlation among data, is more precise and shows lower error and more correlation in relation to the expected output (daily maximum temperature). Also, among other climatic parameters, minimum temperature and the average of the wet temperature indicated the estimation of the daily maximum temperature with lower error and more correlation in comparison to other climatic parameters.
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