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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Model Induction from Data: Towards the Next Generation of Computational Engines in Hydraulics and Hydrology

Model Induction from Data: Towards the Next Generation of Computational Engines in Hydraulics and Hydrology

Dibike, Y. B.
Dibike

Paperback

Technology & EngineeringEnvironmental StudiesGeneral Computers

ISBN10: 9058093565
ISBN13: 9789058093561
Publisher: Routledge
Published: Jan 1 2002
Pages: 156
Weight: 0.64
Height: 0.34 Width: 7.00 Depth: 10.00
Language: English

There has been an explosive growth of methods in recent years for learning (or estimating dependency) from data, where data refers to known samples that are combinations of inputs and corresponding outputs of a given physical system. The main subject addressed in this thesis is model induction from data for the simulation of hydrodynamic processes in the aquatic environment. Firstly, some currently popular artificial neural network architectures are introduced, and it is then argued that these devices can be regarded as domain knowledge incapsulators by applying the method to the generation of wave equations from hydraulic data and showing how the equations of numerical-hydraulic models can, in their turn, be recaptured using artificial neural networks.

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