نوع مقاله : مقاله پژوهشی
نویسندگان
1 عضو هیأت علمی /گروه عمران، دانشگاه آزاد اسلامی واحد ارسنجان
2 دانشیار/ بخش مهندسی راه و ساختمان ، دانشکده مهندسی، دانشگاه شیراز
چکیده
کلیدواژهها
عنوان مقاله [English]
نویسندگان [English]
A proper architectural design of the Artificial Neural Network (ANN) models can provide a robust tool in water resources modeling and forecasting. The performance of different neural networks in a groundwater level forecasting was examined by researchers in order to identify an optimal ANN architecture that can provide accurate predictions up to 24 months ahead. In this study the Saadat-shahrPlain in Fars Province in central Iran was chosen as the study area. All networks were trained for an 8-year period of data and calibrated for a 24-month period. Experimental results showed that the most accurate forecast (for up to 24 months ahead) is achieved with an FNN trained with the LM algorithm
کلیدواژهها [English]