首页> 外文会议>Asia-Pacific Conference on Simulated Evolution and Learning(SEAL'2002); 20021118-22; Singapore(SG) >REFRIGERANT LEAK PREDICTION IN SUPERMARKETS USING EVOLVED NEURAL NETWORKS
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REFRIGERANT LEAK PREDICTION IN SUPERMARKETS USING EVOLVED NEURAL NETWORKS

机译:利用进化的神经网络预测超级市场中的制冷剂泄漏

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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.
机译:商业制冷系统中制冷剂气体的损失是大多数连锁超市的主要维护成本。气体泄漏也会对环境产生不利影响。现有的监视系统会不断监视此类故障,但通常在造成重大损坏之前无法检测到它们。本章介绍了一个系统,该系统使用在中央警报监视中心接收的实际数据来预测气体泄漏的发生。进化算法用于繁殖神经网络,在有限的训练数据下,这些神经网络可以实现非常有用的高精度。

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