AU - Rahmati, Enayatollah AU - Montazeri, Majid AU - Gandomkar, Amir AU - Lshanizand, Mehran TI - Evaporation Predict Using Climate Signals and Artificial Neural Network in Dez Basin PT - JOURNAL ARTICLE TA - Geographical-Researches JN - Geographical-Researches VO - 30 VI - 2 IP - 2 4099 - http://georesearch.ir/article-1-650-en.html 4100 - http://georesearch.ir/article-1-650-en. SO - Geographical-Researches 2 ABĀ  - Evaporation is an important phenomenon in Hydrological cycle and estimation and prediction is necessary for proper planning and management of water, so to predict it's occurred has been in Dez basin that significant part of the water supplies. The simulated evaporation and the possibility of prediction it, using neural network that data of evaporation at 4 station and claimant signals whit at least 19 years monthly analysis. The results show that the most important signals affecting the evaporation basin include: Nina3, Nina1, Sw monsoon, Mei, Nina4 and Nina3.4. Comparison of observed data with a high correlation between the ANN output data shows. So that the correlation of the Khorramabad station is 79%, Dezful 94%, Kuhrang 80%, and Arak 72%. The output data of the neural network and climatic signals, can accurately predict the top 98% of the basin evaporation. CP - IRAN IN - LG - eng PB - Geographical-Researches PG - 261 PT - Original Research YR - 2015