4707

4426

كارشناسي ارشد

هوش مصنوعي و رباتيك

اصفهان: دانشگاه صنعتي اصفهان، دانشكده برق و كامپيوتر

1388

ده،90،[I]ص.: مصور، جدول،نمودار

ص.ع.به فارسي و انگليسي

محمد داورپناه جزي

سحر صدودي

3/8/88

مهندسي برق و كامپيوتر

ID4426

به فارسي و انگليسي: قبل رويت در نسخه ديجيتالي

Temperature Prediction using Downscaling of ECHO model for the next 30 years Somayeh khajeh hassani skhajehasani@ec iut ac ir Date of Submission April 2009 Department of Electical and computer engineering Isfahan University of Technology Isfahan 84156 83111 Iran Degree M Sc Language Farsi Supervisor Dr Mohamad Davarpanah Jazi mdjazi@cc iut ac irAbstract Scientists believe that the increase in the concentration of green house gases in the atmosphere willcause climate changes Global Climate Models GCMs have been developed for predicting thesechanges But the low resolution of the GCMs has made it impossible to be used for hydrologic local studies Most of the GCMs have the resolution of more than 2 2 degrees Due to this lowspatial resolution and the elimination or simplifying of some meso scale events in the atmospheregeneral circulation models these models are unable to offer a correct estimation of the weathercondition of the study region in comparison with the short term and regional models Consequently the model outputs should be downscaled by regional or statistical dynamical modelsup to 50 KMs in the spatial scale or stations So by considering the local effects it would involvethe least errors in general circulation models Therefore downscaling is necessary The objective ofthis study is to offer the ways for improving the downscaling models accuracy There are four methods for downscaling 1 Regression 2 Weather patterns 3 Probabilistic 4 Dynamical Among these methods regression is mostly used because of its simplicity Alsoamong the regression methods the linear regression is simpler than others Hence in this study thismethod would be investigated This model works monthly as due to some limitations the statisticalmodels can t work daily For the daily running of the model the artificial intelligent downscalingcan be used At the second section of this study the neural network has been used for modeling andimproving the models output BF and RBF networks are used for modeling The combination ofneural networks and fuzzy logic has been considered during recent years by scientists and has beenused in many cases This model works on daily basis The combination of neural networks andfuzzy logic has been used for the purpose of improving the models outputs The achieved resultsshow the improving of the offered method in comparison with the previous methods Then by useof this optimum model the tempreture is predicted for the next 30 years and its trend is studied andis compared with the result of the past years Key words green house climate change GCMs meso scale downscale regression statistical Artificial Neural Networks fuzzy logic

محمد داورپناه جزي

سحر صدودي