Title :
Predicting alarms in supermarket refrigeration systems using evolved neural networks and evolved rulesets
Author :
Taylor, Dan W. ; Corne, David W. ; Taylor, David L. ; Harkness, Jack
Author_Institution :
Reading Univ., UK
fDate :
6/24/1905 12:00:00 AM
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
Keywords :
alarm systems; backpropagation; neural nets; refrigeration; refrigerators; alarm prediction; backpropagation trained neural networks; evolved neural networks; evolved rulesets; financial losses; refrigeration controllers; supermarket refrigeration systems; Centralized control; Coolants; Heat pumps; Intelligent networks; Machinery; Monitoring; Neural networks; Refrigerants; Refrigeration; Temperature;
Conference_Titel :
Evolutionary Computation, 2002. CEC '02. Proceedings of the 2002 Congress on
Conference_Location :
Honolulu, HI
Print_ISBN :
0-7803-7282-4
DOI :
10.1109/CEC.2002.1004548
