- author = "Byoung-Tak Zhang and Je-Gun Joung",
- title = "Evolutionary Design of Neural Trees for Heart Rate Prediction",
- booktitle = "Soft Computing in Engineering Design and Manufacturing",
- year = "1997",
- editor = "Pravir K. Chawdhry and Rajkumar Roy and Raj K. Pant",
- pages = "93--101",
- publisher_address = "Godalming, GU7 3DJ, UK",
- month = "23-27 " # jun,
- publisher = "Springer-Verlag London",
- keywords = "genetic algorithms, genetic programming, ANN",
- ISBN = "3-540-76214-0",
-
URL = "
http://www.springer.com/engineering/mechanical+eng/book/978-3-540-76214-0?cm_mmc=Google-_-Book%20Search-_-Springer-_-0",
-
DOI = "
10.1007/978-1-4471-0427-8_11",
- abstract = "Some classes of neural networks are known as universal function approximators. However, their training efficiency and generalisation performance depend highly on the structure which is usually determined by a human designer. In this paper we present an evolutionary computation method for automating the neural network design process. We represent networks as tree structures, called neural trees, in genotype and apply genetic operators to evolve problem-dependent network structures and their weights. Experimental results are provided on the prediction of a heart rate time-series by evolving sigma-pi neural trees.",
-
notes = "WSC2 Second On-line World Conference on Soft Computing
in Engineering Design and Manufacturing. feed forward
artificial neural networks comprised of sigma and pi
nodes evolved using GP. 'Between generations the
network weights are adapted by a stochastic
hill-climbing search.' Fitness based on error between
prediction and measurement on training examples plus
term related to complexity (ie size) of network and the
complexity of the best network in the previous
generation (ie fitness prefers parsimony). 'Without
(the parsimony term) the network size usually grows
without bound'.
wsc2/ind_paper/d_zhang.html URL broken 2005",
- size = "9 pages",
