### Abstract

Original language | English |
---|---|

Title of host publication | Engineering Applications of Neural Networks. EANN 2016 |

Place of Publication | Switzerland |

Publisher | Springer International Publishing |

Pages | 253-266 |

Number of pages | 14 |

ISBN (Electronic) | 9783319441887 |

ISBN (Print) | 9783319441870 |

DOIs | |

Publication status | Published - 19 Aug 2016 |

Event | Engineering Applications of Neural Networks. EANN 2016 - Aberdeen, UK, 2-5 September, 2016 Duration: 19 Aug 2016 → … |

### Publication series

Name | Communications in Computer and Information Sciences |
---|

### Conference

Conference | Engineering Applications of Neural Networks. EANN 2016 |
---|---|

Period | 19/08/16 → … |

### Fingerprint

### Bibliographical note

The final publication is available at link.springer.com### Keywords

- Two-hidden-layer feedforward
- ANN
- Exhaustive search
- Optimal topology
- Optimal node ratio
- Heurix
- Universal function approximation

### Cite this

*Engineering Applications of Neural Networks. EANN 2016*(pp. 253-266). (Communications in Computer and Information Sciences). Switzerland: Springer International Publishing. https://doi.org/10.1007/978-3-319-44188-7_19

}

*Engineering Applications of Neural Networks. EANN 2016.*Communications in Computer and Information Sciences, Springer International Publishing, Switzerland, pp. 253-266, Engineering Applications of Neural Networks. EANN 2016, 19/08/16. https://doi.org/10.1007/978-3-319-44188-7_19

**Accelerated Optimal Topology Search for Two-hidden-layer Neural Networks.** / Thomas, Alan; Walters, Simon; Petridis, Miltiadis; Malekshahi Gheytassi, Mohammad; Morgan, Robert.

Research output: Chapter in Book/Conference proceeding with ISSN or ISBN › Conference contribution with ISSN or ISBN › Research › peer-review

TY - GEN

T1 - Accelerated Optimal Topology Search for Two-hidden-layer Neural Networks

AU - Thomas, Alan

AU - Walters, Simon

AU - Petridis, Miltiadis

AU - Malekshahi Gheytassi, Mohammad

AU - Morgan, Robert

N1 - The final publication is available at link.springer.com

PY - 2016/8/19

Y1 - 2016/8/19

N2 - Two-hidden-layer feedforward neural networks are investigated for the existence of an optimal hidden node ratio. In the experiments, the heuristic n1 =int (0.5nh + 1), where n1 is the number of nodes in the first hidden layer and nh is the total number of hidden nodes, found networks with generalisation errors, on average, just 0.023%-0.056% greater than those found by exhaustive search. This reduced the complexity of an exhaustive search from quadratic, to linear in , with very little penalty. Further reductions in search complexity to logarithmic could be possible using existing methods developed by the Authors

AB - Two-hidden-layer feedforward neural networks are investigated for the existence of an optimal hidden node ratio. In the experiments, the heuristic n1 =int (0.5nh + 1), where n1 is the number of nodes in the first hidden layer and nh is the total number of hidden nodes, found networks with generalisation errors, on average, just 0.023%-0.056% greater than those found by exhaustive search. This reduced the complexity of an exhaustive search from quadratic, to linear in , with very little penalty. Further reductions in search complexity to logarithmic could be possible using existing methods developed by the Authors

KW - Two-hidden-layer feedforward

KW - ANN

KW - Exhaustive search

KW - Optimal topology

KW - Optimal node ratio

KW - Heurix

KW - Universal function approximation

U2 - 10.1007/978-3-319-44188-7_19

DO - 10.1007/978-3-319-44188-7_19

M3 - Conference contribution with ISSN or ISBN

SN - 9783319441870

T3 - Communications in Computer and Information Sciences

SP - 253

EP - 266

BT - Engineering Applications of Neural Networks. EANN 2016

PB - Springer International Publishing

CY - Switzerland

ER -