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

I have wriiten a number of articles for TheConversation
http://bit.ly/1yWlOkE
Can ants play chess? Yes they can!
http://bit.ly/1yW3UhX

Latest Blog Post

Snooker: Celebrating 40 years at the Crucible

Random Blog Post

A compound framework for sports results prediction: A football case study

Publication(s)

A New Model and a Hyper-heuristic Approach for Two-dimensional Shelf Space Allocation
http://bit.ly/1h1JAhT
Searching the Hyper-heuristic Design Space
http://bit.ly/1sD4RoY
Engineering Design of Strategies for Winning Iterated Prisoner’s Dilemma Competitions
http://bit.ly/1goRemG
An adaptive multi-population artificial bee colony algorithm for dynamic optimisation problems
http://bit.ly/29btjbV

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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doi

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URL

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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} }