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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Streamflow Forecasting Based on Artificial Neural Networks, purposes and for real time operation of water resources systems. Forecasts, with lead times ranging from weeks to months, are generally used for water system planning and management, such as allocation of irrigation water, hydropower planning, and drought analysis and mitigation.

Inoperable

Modular Neural Networks for Watershed Runoff,cipitation, temperature, etc.) of the region. The influence of all these factors is not understood clearly. As a consequence, there exists some skepticism in the use of physically-based models for predicting watershed runoff (Grayson et al., 1992).

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Book 2000ion of artificial neural networks (ANNs), as we understand them today, was perhaps first formalized by McCulloch and Pitts (1943) in their 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 an

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https://doi.org/10.1007/BFb0108003r 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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https://doi.org/10.1007/BFb0108003l predictions, power systems, and pattern recognition among others (Kosko, 1992; Refenes et al., 1994; Saund, 1989; Schalkoff, 1992; Suykens et. al. 1996; Vemuri and Rogers 1994). These successes have also inspired applications to water resources and environmental systems (Achela et al., 1998; Chang

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Advances in Solid State Physicsesources systems. Depending on the lead time, the forecast can be real time, (i.e., near-real time or online), short term and long term. Real time forecasting has applications in operational flood as well as drought management. It can forewarn extreme flood as well as drought conditions, and can hel

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Advances in Solid State Physicss. Frequent droughts and floods of 1993 in Kansas and other midwestern U.S. are testimonies to the need for good predictive models at the watershed scale. The response of a watershed to precipitation is complicated by various hydrologic components that are distributed within it in a heterogeneous ma