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

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.