Graham Kendall
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Professor Graham Kendall

Professor Graham Kendall is the Provost and CEO of The University of Nottingham Malaysia Campus (UNMC). He is also a Pro-Vice Chancellor of the University of Nottingham.

He is a Director of MyResearch Sdn Bhd, Crops for the Future Sdn Bhd. and Nottingham Green Technologies Sdn Bhd. He is a Fellow of the British Computer Society (FBCS) and a Fellow of the Operational Research Society (FORS).

He has published over 230 peer reviewed papers. He is an Associate Editor of 10 journals and the Editor-in-Chief of the IEEE Transactions of Computational Intelligence and AI in Games.

News

How are university examinations scheduled?
http://bit.ly/1z0pG4s
A Conversation article celebrating Pi
http://bit.ly/1DXuXbV

Latest Blog Post

Snooker: Celebrating 40 years at the Crucible

Random Blog Post

Conjuring Trick

Publication(s)

Document Zone Classification for Technical Document Images Using Artificial Neural Network and Support Vector Machines
http://bit.ly/1eUn8rs
Chapter 4: Genetic Algorithms
http://bit.ly/1h1JBCi
A Tabu Search Hyper-heuristic Approach to the Examination Timetabling Problem at the MARA University of Technology
http://bit.ly/fA5Mv6
Learning with imperfections - a multi-agent neural-genetic trading system with differing levels of social learning
http://bit.ly/hBQypU

Graham Kendall: Details of Requested Publication


Citation

Kendall, G; Binner, J and Gazely, A.M Evolutionary Strategies vs. Neural Networks: An Inflation Forecasting Experiment. In Proceedings of the International Conference on Artificial Intelligence (IC-AI'2001), pages 609-615, CSREA Press, 25-28 June 2001, Monte Carlo Resort & Casino, Las Vegas, Nevada, USA, 2001.


Abstract

Previous work has used neural networks to predict the rate of inflation in Taiwan using four measures of ‘money’ (simple sum and three divisia measures). In this work we develop a new approach that uses an evolutionary strategy as a predictive tool. This approach is simple to implement yet produces results that are favourable with the neural network predictions. Computational results are given.


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Bibtex

@INPROCEEDINGS{kbg2001a, author = {G. Kendall and J. Binner and A.M. Gazely},
title = {Evolutionary Strategies vs. Neural Networks: An Inflation Forecasting Experiment},
booktitle = {Proceedings of the International Conference on Artificial Intelligence (IC-AI'2001)},
year = {2001},
editor = {H.R. Arabnia},
pages = {609--615},
address = {25-28 June 2001, Monte Carlo Resort \& Casino, Las Vegas, Nevada, USA},
month = {June 25-28},
publisher = {CSREA Press},
abstract = {Previous work has used neural networks to predict the rate of inflation in Taiwan using four measures of ‘money’ (simple sum and three divisia measures). In this work we develop a new approach that uses an evolutionary strategy as a predictive tool. This approach is simple to implement yet produces results that are favourable with the neural network predictions. Computational results are given.},
comment = {ISBN 1-892512-79-3},
keywords = {prediction, inflation, evolution strategy, divisia, forecasting},
timestamp = {2007.03.29},
webpdf = {http://www.graham-kendall.com/papers/kbg2001a.pdf} }