Titlebook: Artificial Neural Networks in Hydrology; R. S. Govindaraju,A. Ramachandra Rao Book 2000 Springer Science+Business Media B.V. 2000 artifici

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Optimal Groundwater Remediation Using Artificial Neural Networks,ment or control strategies possibilities for ones that meet management goals while minimizing cost. The main advantage of applying these mathematical tools to decision-making problems is that they are less restricted by human imagination than case-by-case comparisons. As the number of competing engi

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Application of Artificial Neural Networks to Forecasting of Surface Water Quality Variables: Issuesbe based, where possible, on relationships that have a physical basis. Recently, artificial neural networks (ANNs) have emerged as alternatives to traditional statistical models in a variety of fields, including water quality modeling.

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Book 2000all fronts: theoretical development of different learning algorithms, computing capabilities, and applications to diverse areas from neurophysiology to the stock market. . Initial studies on artificial neural networks were prompted by adesire to have computers mimic human learning. As a result, the

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Introduction,r model of an artificial neuron. Research in this field remained somewhat dormant in the early years, perhaps because of the limited capabilities of this method and because there was no clear indication of its potential uses. However, interest in this area picked up momentum in a dramatic fashion wi

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