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

What do we spend so much in supermarkets?
http://bit.ly/1yW6If7
I have published a few papers on Sports Scheduling.
http://bit.ly/gVaUqT

Latest Blog Post

How Isaac Newton could help you beat the casino at roulette

Random Blog Post

Wisdom of the Crowds at the Graduate School Christmas Party

Publication(s)

Youth Sports Leagues Scheduling
http://bit.ly/f1i7SE
A dynamic truck dispatching problem in marine container terminal
http://bit.ly/2mH037B
Evolving human-competitive reusable 2D strip packing heuristics
http://bit.ly/f4msct
The optimisation of the single surface mount device placement machine in printed circuit board assembly: a survey
http://bit.ly/fRZIdH

Graham Kendall: Details of Requested Publication


Citation

Binner, J; Chen, Q- and Kendall, G Evolving Weights for a new UK Divisia. In In Proceedings of the 7th International Conference on Computational Intelligence in Economics and Finance, pages 179-185, Kainan University, Taoyuan, Taiwan, 2008.


Abstract

Divisia money is a monetary aggregate that gives each component an assigned weight. We use an evolutionary neural network to calculate new Divisia weights for each component utilising the Bank of England monetary data for the U.K. We propose a new money aggregate using our newly derived weights to carry out quantitative inflation prediction. The results show that this new money aggregate has better inflation forecasting performance than the traditionally constructed Bank of England Divisia money.


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Bibtex

@INPROCEEDINGS{bck2008, author = {J. Binner and Q-B Chen and G. Kendall},
title = {Evolving Weights for a new UK Divisia.},
booktitle = {In Proceedings of the 7th International Conference on Computational Intelligence in Economics and Finance},
year = {2008},
pages = {179--185},
address = {Kainan University, Taoyuan, Taiwan},
month = {5-7 Dec 2008, Kainan University, Taoyuan, Taiwan},
abstract = {Divisia money is a monetary aggregate that gives each component an assigned weight. We use an evolutionary neural network to calculate new Divisia weights for each component utilising the Bank of England monetary data for the U.K. We propose a new money aggregate using our newly derived weights to carry out quantitative inflation prediction. The results show that this new money aggregate has better inflation forecasting performance than the traditionally constructed Bank of England Divisia money.},
keywords = {Divisia, inflation, prediction, neural networks, artificial neural networks},
owner = {est},
timestamp = {2010.03.18},
webpdf = {http://www.graham-kendall.com/papers/bck2008.pdf} }