Predicting alarms in supermarket refrigeration systems using evolved neural networks and evolved rulesets

Authors:
D. W. Taylor;D. W. Corne;D. L. Taylor;J. Harkness
Affiliations:
Reading Univ., UK;Reading Univ., UK;Centre for Computational Neurosciences & Robotics, Sussex Univ., Brighton, UK;Centre for Multimedia Signal Process., Hong Kong Polytech.Univ., Kowloon, China
Venue:
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Year:
2002

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Abstract

Supermarkets suffer serious financial losses owing to problems with their refrigeration systems. Most refrigeration units have controllers which output "high-temperature" and similar alarms. We describe a system developed to predict alarm volumes from this data in advance, and compare evolved and backpropagation-trained neural networks, and evolved rulesets for this task.