The neural network technique - 1: a general exposition

Date

2004-01-01

Author

Tulunay, Yurdanur
Tulunay, E
Senalp, ET

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Near earth space processes are highly complex and nonlinear and mathematical modeling based on first physical principals is usually difficult or impossible. For such cases data driven modeling methods are recommended to be used in parallel with mathematical modeling approach. Highly non-linear processes in the near-earth space are advantageously dealt with using data-driven modeling techniques in the neural network (NN) approach. The only basic requirement for its application is the availability of representative data. (C) 2003 COSPAR. Published by Elsevier Ltd. All rights reserved.

Subject Keywords

Space and Planetary Science, Aerospace Engineering

URI

https://hdl.handle.net/11511/56982

Journal

PATH TOWARD IMPROVED IONOSPHERE SPECIFICATION AND FORECAST MODELS

DOI

https://doi.org/10.1016/j.asr.2003.06.008

Collections

Graduate School of Natural and Applied Sciences, Article

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Citation Formats

Y. Tulunay, E. Tulunay, and E. Senalp, “The neural network technique - 1: a general exposition,” PATH TOWARD IMPROVED IONOSPHERE SPECIFICATION AND FORECAST MODELS, pp. 983–987, 2004, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/56982.