Similar Search Results

Effect of Global Warming on Intensity and Frequency Curves of Precipitation, Case Study of Northwestern Iran

Roshan, Gholamreza; Ghanghermeh, AbdolAzim; Nasrabadi, … - In: Water Resources Management 27 (2013) 5, pp. 1563-1579

such natural hazards in northwestern Iran is considered in this study through clustering the precipitation regime. To … downscaled using the LARS-WG model. The method for comparing precipitations was done based on clustering in the form of 5 …

Persistent link: https://www.econbiz.de/10010997820

Identification of Homogeneous Rainfall Regimes in Northeast Region of India using Fuzzy Cluster Analysis

Goyal, Manish; Gupta, Vivek - In: Water Resources Management 28 (2014) 13, pp. 4491-4511

clustering algorithm (FCM). A comparison is also performed using K- Mean clustering algorithm. Additionally, regional homogeneity …

Persistent link: https://www.econbiz.de/10010998139

Geoinformatic Intelligence Methodologies for Drought Spatiotemporal Variability in Greece

Kanellou, Efrosyni; Spyropoulos, Nicos; Dalezios, Nicolas - In: Water Resources Management 26 (2012) 5, pp. 1089-1106

goal is to use the PCA + clustering method to transform the RDI temporal data (1982–2001) and cluster the different regions … indices followed by Clustering that was based on certain eigenchannels resulted from the previous PCA analysis. Both methods …

Persistent link: https://www.econbiz.de/10010794247

Forecasting Surface Water Level Fluctuations of Lake Van by Artificial Neural Networks

Altunkaynak, Abdüsselam - In: Water Resources Management 21 (2007) 2, pp. 399-408

Lake Van in eastern Turkey has been subject to water level rise during the last decade and, consequently, the low-lying areas along the shore are inundated, giving problems to local administrators, governmental officials, irrigation activities and to people's property. Therefore, forecasting...

Persistent link: https://www.econbiz.de/10010997328

River Suspended Sediment Prediction Using Various Multilayer Perceptron Neural Network Training Algorithms—A Case Study in Malaysia

Mustafa, M.; Rezaur, R.; Saiedi, S.; Isa, M. - In: Water Resources Management 26 (2012) 7, pp. 1879-1897

sediment prediction using MLP networks. However, LM was the faster (1/7 of SCG convergence time) of the two algorithms …

Persistent link: https://www.econbiz.de/10010997800

Water Consumption Prediction of Istanbul City by Using Fuzzy Logic Approach

Altunkaynak, Abdüsselam; Özger, Mehmet; Çakmakci, Mehmet - In: Water Resources Management 19 (2005) 5, pp. 641-654

fluctuations of Istanbul city in Turkey. In the prediction procedure only lag one is considered. It is observed that the TS fuzzy …

Persistent link: https://www.econbiz.de/10010997834

Statistical Prediction of Changes in Water Resources Trends Based on Set Pair Analysis

Feng, L.; Sang, G.; Hong, W. - In: Water Resources Management 28 (2014) 6, pp. 1703-1711

actual value of the average annual discharge grade at Yamadu Station, which showed that the prediction was valid. It … the prediction that it was a dry year. Three physical factors were not processed using set pair analysis so they could be …> </InlineEquation> for the average annual discharge grade at Yamadu Station during 1953–1974. It’s known that the prediction of the …

Persistent link: https://www.econbiz.de/10010997878

Stage and Discharge Forecasting by SVM and ANN Techniques

Aggarwal, S.; Goel, Arun; Singh, Vijay - In: Water Resources Management 26 (2012) 13, pp. 3705-3724

In this study, forecasting of stage and discharge was done in a time-series framework across three time horizons using three models: (i) persistence model, (ii) feed-forward neural network (FFNN) model, and (iii) support vector machine (SVM) model. For these models, lagged values of the time...

Persistent link: https://www.econbiz.de/10010847383

Prediction of Ground Water Levels in the Uplands of a Tropical Coastal Riparian Wetland using Artificial Neural Networks

Karthikeyan, L.; Kumar, D.; Graillot, Didier; Gaur, Shishir - In: Water Resources Management 27 (2013) 3, pp. 871-883

Artificial Neural Networks (ANNs) have been found to be a robust tool to model many non-linear hydrological processes. The present study aims at evaluating the performance of ANN in simulating and predicting ground water levels in the uplands of a tropical coastal riparian wetland. The study...

Persistent link: https://www.econbiz.de/10010794059

Prediction of Urmia Lake Water-Level Fluctuations by Using Analytical, Linear Statistic and Intelligent Methods

Kakahaji, Hossein; Banadaki, Hamed; Kakahaji, Abbas; … - In: Water Resources Management 27 (2013) 13, pp. 4469-4492

exogenous input (ARX) and Box-Jenkins (BJ) models are employed with the same mentioned inputs for prediction purpose. In … applied to investigate capability of intelligent nonlinear methods for lake level changes prediction. All models performances …

Persistent link: https://www.econbiz.de/10010794070