Open Daily: 10am - 10pm | Alley door 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

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Time Series Analysis using Neural Networks

Time Series Analysis using Neural Networks

Vijay, Ritu

Paperback

Applications

ISBN10: 3659211818
ISBN13: 9783659211812
Publisher: Lap Lambert Academic Pub
Published: Aug 11 2012
Pages: 60
Weight: 0.22
Height: 0.14 Width: 6.00 Depth: 9.00
Language: English
Artificial neural networks are suitable for many tasks in pattern recognition and machine learning. Unlike conventional techniques for time series analysis, an artificial neural network needs little information about the time series data and can be applied to a broad range of problems. The usage of artificial neural networks for time series analysis relies purely on the data that were observed. As Radial Basis networks with one hidden layer is capable of approximating any measurable function. An artificial neural network is powerful enough to represent any form of time series. The capability to generalize allows artificial neural networks to learn even in the case of noisy and/or missing data. Another advantage over linear models is the network's ability to represent nonlinear time series. Prediction of tides is very much essential for human activities and to reduce the construction cost in marine environment. This book presents an application of the artificial neural network with Radial basis function for accurate prediction of tides. This neural network model predicts the time series data of hourly tides directly while using an an efficient learning process.

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