The loss of refrigerant gas from commercial refrigeration systems is a major maintenance cost for most supermarket chains. Gas leaks can also have a detrimental effect on the environment. Existing monitoring systems maintain a constant watch for faults such as this, but often fail to detect them until major damage has been caused. This chapter describes a system which uses real-world data received at a central alarm monitoring centre to predict the occurrence of gas leaks. Evolutionary algorithms are used to breed neural networks which achieve usefully high accuracies given limited training data.
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