Proceedings of the 2018 International Conference on Computer Modeling, Simulation and Algorithm (CMSA 2018)

The Selection of Neural Network Input Parameters Based on Association Rules

Authors
Lei Shi
Corresponding Author
Lei Shi
Available Online April 2018.
DOI
10.2991/cmsa-18.2018.72How to use a DOI?
Keywords
neural network; association rules; parameter selection; dimension reduction
Abstract

Neural network has strong ability of nonlinear approximation and fitting, which was widely used in various prognosis prediction researches. Meanwhile, the selection of neural network input parameters was very important: the number of input layer nodes would increase as the number of input parameters and it required a large number of sample data to train the neural network, which was very easy to cause the dimension disaster. Otherwise, the sample data and the local extremums in the process of convergence would decrease as the number of input parameters, which could simplify the topology of the neural network prediction model greatly. In this paper, we used association rules based on data mining to select input parameters of the neural network prediction model of cervical spinal cord injury and reduced its dimensionality from 25 to 7. Finally, the good performance is proved through the simulation results using MATLAB.

Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2018 International Conference on Computer Modeling, Simulation and Algorithm (CMSA 2018)
Series
Advances in Intelligent Systems Research
Publication Date
April 2018
ISBN
10.2991/cmsa-18.2018.72
ISSN
1951-6851
DOI
10.2991/cmsa-18.2018.72How to use a DOI?
Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Lei Shi
PY  - 2018/04
DA  - 2018/04
TI  - The Selection of Neural Network Input Parameters Based on Association Rules
BT  - Proceedings of the 2018 International Conference on Computer Modeling, Simulation and Algorithm (CMSA 2018)
PB  - Atlantis Press
SP  - 317
EP  - 319
SN  - 1951-6851
UR  - https://doi.org/10.2991/cmsa-18.2018.72
DO  - 10.2991/cmsa-18.2018.72
ID  - Shi2018/04
ER  -