نوع مقاله : مقاله پژوهشی
نویسندگان
1 دانشجوی کارشناسی ارشد مهندسی منابع آب دانشگاه شهید چمران اهواز
2 گروه هیدرولوژی و منابع آب دانشگاه شهید چمران اهواز
3 استادیار گروه هیدرولوژی و منابع آب دانشگاه شهید چمران
4 استادیارگروه هیدرولوژی و منابع آب دانشگاه شهید چمران اهواز
چکیده
کلیدواژهها
عنوان مقاله [English]
نویسندگان [English]
Due to the importance of groundwater resources, in order to calculate the average level and estimate the water level in plains, it is necessary to generalize the information collected from point to the plain. Application of geostatistical models has always been associated with error, because the fitness function given in most cases is not include all the experimental. The aim of this study is An investigation on the application of combined geostatistics with optimized Artificial Neural Networks by genetic algorithm in interpolation of groundwater level in Ramhormoz plain. The obtained results from Kriging, Cokriging and IDW methods, are shown cokriging with the Gaussian variogeram in Ramhormoz Plain are the best geostatistical method to estimate the groundwater level and combined with neural networks. results the combination of these two models showed that combined optimized model by genetic algorithm possesses have better evaluation criteria than geostatistical methods to estimate groundwater level and proposed As a reasonable combined model to an estimate of the groundwater level.
کلیدواژهها [English]