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Artificial Neural Network Model of Maximum Temperature Using NOAA data


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Год выпуска: 2014
Автор: Mohammad Ebrahim Banihabib,Azar Arabi,Ali A. Salha and Ali Rahimikhoob
Издательство: LAP Lambert Academic Publishing
Страниц: 92
ISBN: 9783659618741
Описание
 The main objective of this book and its case study is to present artificial neural networks (ANNs) model using National Oceanic and Atmospheric Administration (NOAA) satellite data to estimate maximum daily air temperature. The proposed model applied in Lake Urmia basin, Iran. The book will take us step by step on how ANNs were used as a new method. In addition to the introduction and the amount of literature review provided, a model with suitable architecture and efficient learning with enough collected data was developed to evaluate the relationships between temperature and parameters influencing the temperature. In brief, air temperature measured in standard climatology stations is one of main descriptive of the environment status. This parameter is of great importance nearby land surface since it regulates many earth processes such as photosynthesis and evapotranspiration. The measured air temperature in climatology stations - which indicates air temperature in vicinity of the...

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