Inspection of temperature alteration and it’s prediction possibility in Ardebil province using statistical analysis and adaptive neuro -fuzzy inference system
author
Abstract:
Temperature alteration plays special role as one of the most basic climate elements. So inspection of temperature alteration and anticipation has scientific- applied magnitude. In this study inspection of several cases of statistical characteristics of monthly average, maximum and minimum temperature and illumination of their alteration method, temperatures predictability by ANFIS is evaluated. Applied data is over 288 months during 24 years of statistical period since January of 1987 until December of 2010 through synoptic stations of Pars Abad, Ardebil and Khalkhal. According to equations of data lineal process, lineal process of temperatures through all of the stations is positive and additive. Lineal process gradient in minimum temperature is more than other maximum and average temperature. Less amplitude more variance and standard aviation and data predictability is more. According to present article adaptive Neuro – fuzzy inference system mostly has acceptable function through anticipation of monthly minimum, maximum and average temperature in the stations of Ardebil province.
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Journal title
volume 16 issue 42
pages 27- 40
publication date 2016-12
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