پديد آورنده :
گل محمدي، محمد حسين
عنوان :
استفاده از سيستم استنتاج فازي بر پايه شبكه عصبي تطبيقي ﴿ANFIS﴾ صحت مدل سازي سري هاي زماني چند متغيره هيدرولوژيكي
مقطع تحصيلي :
كارشناسي ارشد
محل تحصيل :
اصفهان: دانشگاه صنعتي اصفهان، دانشكده عمران
صفحه شمار :
نه،106ص.:مصور،جدول،نمودار
استاد راهنما :
حميدرضا صفوي
توصيفگر ها :
پيش بيني , تك متغيره , شبكه هاي عصبي مصنوعي
تاريخ نمايه سازي :
17/3/89
استاد داور :
كيوان اصغري،بنفشه زهرايي
چكيده فارسي :
به فارسي و انگليسي: قابل رويت در نسخه ديجيتالي
چكيده انگليسي :
Application of Adaptive Neuro Based Fuzzy Inference System ANFIS for Hydrological Multivariate Time Series Modeling Mohammad Hossein Golmohammadi m golmohammadi@cv iut ac ir Date of Submission 27 February 2010 Department of Civil Engineering Isfahan University of Technology Isfahan 84156 83111 IranDegree M Sc Language FarsiSupervisor Dr Hamid Reza Safavi hasafavi@cc iut ac irAdvisor Dr Maryam Zekri mzekri@cc iut ac irAbstract The Modeling and prediction by time series analysis has been an important role in lastdecades and has wide applications in different fields of science and engineering such ashydrology So that parameter estimation of various time series models is one of theessential step of modeling The presented methods in this field such as method ofmoments have complicated formula in spatial and temporal multivariate models particulary so this need a lot of time and survey of different formula for each model Inthis study by using Adaptive Neuro Based Fuzzy Inference Systems ANFIS a new andeffective method for parameter estimation of various univariate and multivariate timeseries models is presented Performance of this technique has surveyed by hydrologicdata of the Zayanedrood river basin and then parameters of the models have estimated After this prediction of the time series has done by using these models In addition prediction of time series has done by ANFIS and MultiLayer Perceptron MLP too andthen the results have compared For comparison of results Mean Absolute Error MAE criterion is used Results of simulations show that presented method in this study can beused as an intelligent and effective technique for univariate and multivariate time seriesmodeling Keywords Hydrological Time Series Prediction Univariate Multivariate AdaptiveNeuro Based Fuzzy Inference System ANFIS Neural Networks
استاد راهنما :
حميدرضا صفوي
استاد داور :
كيوان اصغري،بنفشه زهرايي
