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
I have wriiten a number of articles for TheConversation
http://bit.ly/1yWlOkE

Latest Blog Post

Snooker: Celebrating 40 years at the Crucible

Random Blog Post

Christmas 2015: Advent calendar of research

Publication(s)

Backward Induction and Repeated Games With Strategy Constraints: An Inspiration From the Surprise Exam Paradox
http://bit.ly/1ib50Nd
An experimental study of hyper-heuristic selection and acceptance mechanism for combinatorial t -way test suite generation
http://bit.ly/2qeXUC5
Combining Examinations to Accelerate Timetable Construction
http://bit.ly/e5KkBg
Solving a Practical Examination Timetabling Problem: A Case Study
http://bit.ly/gnJ9XG

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} }