Successful river flow forecasting is a major goal and an essential procedure that is necessary in water resource planning and management. There are many forecasting techniques used for river flow forecasting. This study proposed a hybrid model based on a combination of two methods: Self Organizing Map (SOM) and Least Squares Support Vector Machine (LSSVM) model, referred to as the SOM-LSSVM mod...

Awareness of the level of river flow and its fluctuations at different times is one of the significant factor to achieve sustainable development for water resource issues. Therefore, the present study two hybrid models, Wavelet- Adaptive Neural Fuzzy Interference System (WANFIS) and Wavelet- Artificial Neural Network (WANN) are used for flow prediction of Gamasyab River (Nahavand, Hamedan, Iran...

Understanding large-scale patterns in flow intermittence is important for effective river management. The duration and frequency of zero-flow periods are associated with the ecological characteristics of rivers and have important implications for water resources management. We used daily flow records from 628 gauging stations on rivers with minimally modified flows distributed throughout France...

flow river forecasting plays an important role in designing, management, and utilization of water resources. the main object of the research is to study the possibility of forecasting and monitoring the northern karon rivers (armand and bazfat) discharge by using modern simulation methods. in this research, armand and bazoft discharge variations was investigated. in this regard, monthly data of...

This paper investigates the application of partially recurrent artificial neural networks (ANN) in the flow estimation for São Francisco River that feeds the hydroelectric power plant of Sobradinho. An Elman neural network was used suitably arranged to receive samples of the flow time series data available for São Francisco River shifted by one month. For that, the neural network input had a de...