Microgenetic algorithms and artificial neural networks to assess minimum data requirements for prediction of pesticide concentrations in shallow groundwater on a regional scale
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چکیده
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Prediction and modeling of fluoride concentrations in groundwater resources using an artificial neural network: a case study in Khaf
Background: One issue of concern in water supply is the quality of water. Measuring the qualitative parameters of water is time-consuming and costly. Predicting these parameters using various models leads to a reduction in related expenses and the presentation of overall and comprehensive statistics for water resource management. Methods: The present study used an artificial neural...
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Comparison of Genetic and Hill Climbing Algorithms to Improve an Artificial Neural Networks Model for Water Consumption Prediction
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A method to predict groundwater vulnerability to pesticide contamination on a regional scale has been developed and applied to a part of the upper Rhone river valley in Western Switzerland. Ž . Stochastic application of deterministic pesticide leaching models Monte-Carlo , along with geostatistical interpolation techniques, were used to map both vulnerability levels and uncertainŽ ties. The var...
متن کاملMonitoring of Regional Low-Flow Frequency Using Artificial Neural Networks
Ecosystem of arid and semiarid regions of the world, much of the country lies in the sensitive and fragile environment Canvases are that factors in the extinction and destruction are easily destroyed in this paper, artificial neural networks (ANNs) are introduced to obtain improved regional low-flow estimates at ungauged sites. A multilayer perceptron (MLP) network is used to identify the funct...
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ژورنال
عنوان ژورنال: Water Resources Research
سال: 2008
ISSN: 0043-1397
DOI: 10.1029/2007wr005875