Title : ( the application of factor analysis and artificial neural networks in predicting spring percipitation by means of climatic parameters of the upper )
Authors: مجید حبیبی نوخندان , عباس فللاح قالهری , Mohammad Mousavi Baygi ,
Full TextAbstract
this research aims to study the relationship between climatic large sals synoptic patterns of upper levels of atmosphere and rainfal in khorasane razavirovince. artificial neural networks and factor analysis were used in this study to predict rainfall in the period between apriland june in the province. at the first the relationship between average rainfal and the changes in the synoptic patterns including the temperature of 700 mb level , the thickness between 500 and 1000 mb level and the relative humidity of 300 mb level were analyzed.
Keywords
, Rainfall prediction, synoptic patterns, Artificial neural networks, factor analysis
@article{paperid:1010939,
author = {مجید حبیبی نوخندان and عباس فللاح قالهری and Mousavi Baygi, Mohammad},
title = {the application of factor analysis and artificial neural networks in predicting spring percipitation by means of climatic parameters of the upper},
journal = {Trends in Applied Sciences Research},
year = {2009},
volume = {4},
number = {2},
month = {August},
issn = {1819-3579},
pages = {85--97},
numpages = {12},
keywords = {Rainfall prediction; synoptic patterns; Artificial neural networks; factor analysis},
}
%0 Journal Article
%T the application of factor analysis and artificial neural networks in predicting spring percipitation by means of climatic parameters of the upper
%A مجید حبیبی نوخندان
%A عباس فللاح قالهری
%A Mousavi Baygi, Mohammad
%J Trends in Applied Sciences Research
%@ 1819-3579
%D 2009
