@inproceedings{d3f977a924ac4944bfa55550842462fe,
title = "Accelerated Optimal Topology Search for Two-hidden-layer Neural Networks",
abstract = "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",
keywords = "Two-hidden-layer feedforward, ANN, Exhaustive search, Optimal topology, Optimal node ratio, Heurix, Universal function approximation",
author = "Alan Thomas and Simon Walters and Miltiadis Petridis and \{Malekshahi Gheytassi\}, Mohammad and Robert Morgan",
note = "The final publication is available at link.springer.com; Engineering Applications of Neural Networks. EANN 2016 ; Conference date: 19-08-2016",
year = "2016",
month = aug,
day = "19",
doi = "10.1007/978-3-319-44188-7\_19",
language = "English",
isbn = "9783319441870",
series = "Communications in Computer and Information Sciences",
publisher = "Springer International Publishing",
pages = "253--266",
booktitle = "Engineering Applications of Neural Networks. EANN 2016",
}