River flow forecasting
Comparison of different forms of the Multi layer Feed Forward Neural Network method used for river flow forecasting
... for river flow forecasting, such as those based on various neural network configurations, illustrates the clear perception among hydrologists that no single superior model has yet been ...
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A hybrid model of self organizing maps and least square support vector machine for river flow forecasting
... ture river flows by using data-driven ...future river flows. For example, Kisi and Cimen (2010) used the monthly river flow data of Canakdere River and Goksudere River in their ...
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Ideal point error for model assessment in data driven river flow forecasting
... for river level flood forecasting on the Lower Mekong River; Nguyen and Chua, ...many river flow forecasting problems, this is of primary concern, and it may, therefore, be ...
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Empirical mode decomposition with least square support vector machine model for river flow forecasting
... River flow is a fundamental component of a water resource ...the river flow is always important for a thorough planning and smooth operation of the water resource ...future river ...
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Applicability of Galway River Flow Forecasting and Modeling System (GFFMS) for Lake Tana Basin, Ethiopia
... Flow forecasting is used in activities requiring stream flow data such as irriga- tion development, water supply, and flood control and hydropower develop- ...time flow forecasting with ...
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Comparison of Artificial Intelligence Techniques for river flow forecasting
... Seyhan River and Cine River, were chosen. For the Seyhan River, daily river flow records measured at the time period 1986–2000 years are used to establish the river flow ...
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Support Vector Regression Integrated with Fruit Fly Optimization Algorithm for River Flow Forecasting in Lake Urmia Basin
... Monthly river flow forecasting using artificial neural network and support vector regression models. 316[r] ...
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River flow forecasting with artificial neural networks using satellite observed precipitation pre processed with flow length and travel time information: case study of the Ganges river basin
... of flow length and travel time as a pre-processing step for incorporating spa- tial precipitation information into Artificial Neural Network (ANN) models used for river flow ...for flow fore- ...
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Multi model data fusion for river flow forecasting: an evaluation of six alternative methods based on two contrasting catchments
... effective. Forecasting enhancements were applied to a range of medium-scale and large-scale flood events; such items were not well modelled in the original ...solutions. Forecasting also included ...
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Daily river flow forecasting in a semi-arid region using twodatadriven
... for forecasting in many areas of science and engineering and are applied in many fields like financial management, manufacturing, control systems, design, environmental science and pattern recognition in, for ...
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River Flow Forecasting Using Long Short term Memory
... Jinghe river. The latter is a tributary of the Yellow River located in the central Loess Plateau and crosses three provinces (Ningxia, Shaanxi and ...
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4. Manning Roughness Coefficient Study on Materials Non Cohesive with Using Entropy to Open Channel Fl
... River flow forecasting is a very important step in order to improve management policies directed to the use of water resources as well as for mitigation, prevention and defense measures against ...
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Three layer wavelet based modeling for river flow
... River flow forecasting is unarguably considered crucial in providing the information required for the design and operation of river ...of flow, flow velocity, and forces from ...
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Impacts of combining meteorological and hydrometric data on the accuracy of streamflow modeling
... Understanding the governing properties of watershed hydrology under different conditions is a challenging issue throughout the globe (Huo et al., 2012; Danandeh Mehr et al., 2013; Moatamednia et al., 2015; Ghorbani et ...
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Evaluation of artificial neural network techniques for flow forecasting in the River Yangtze, China
... the River Yangtze at Yichang (upstream of the Three Gorges Dam) for the period 1991 to 1993, it is shown that both neural network types can simulate river flows beyond the range of the training ...for ...
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Redressing the balance: quantifying net intercatchment groundwater flows
... of flow leaving catch- ments as groundwater export and up to 50 % of river flow originating from groundwater imported from other ...groundwater flow and transport modeling (Gleeson and ...
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Short term traffic flow forecasting with A SVARMA
... The proposed Bayesian A-SVARMA methodology has been evaluated by modelling traffic volume observations from a busy thoroughfare in the city centre of Dublin in Ireland. Two datasets corresponding to two chosen sections ...
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An Approach for Flow Forecasting in Ungauged Catchments – A Case Study for Ho Ho reservoir catchment, Ngan Sau River, Central Vietnam
... MIKE NAM, a lumped model, developed at DHI Water & Environment has been widely used in researches [Keskin et al. 2007, Liu et al. 2007, Kamel et al. 2008]. The model simulates the water movement in the land phase of ...
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Flow and salinity in the Murray river : Study of flow and salt loads in the Murray River of the Murray Darling Basin
... high flow, the salinity is less than during low flows but does not decrease very fast and still has some ...the river becomes a continuous series of weir pools between Lock 9 and Lock 1 where Lock 5 is in ...
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Characteristics and Causes of Disastrous Debris Flows on July 4, 2013, in Shimian County, Sichuan, China
... The gullies of Hou, Heilinzi and Xiongjia are located at the right bank of Nanya River, a tributary of Dadu River. Only 6 km upstream to the Shimian County (Figure 1), the three gullies are featured with ...
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