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Predictive Classification of Future Operations

机译:未来业务的预测分类

摘要

A system evaluates a plurality of faults in an operation of a machine at a set of future instances of time. The system uses a neural network including a first subnetwork sequentially connected with a sequence of second subnetworks for each of the future instance of time such that an output of one subnetwork is an input to a subsequent subnetwork. The first subnetwork accepts the current time-series data and the current setpoints of operation of the machine. Each of the second subnetworks accepts the output of a preceding subnetwork, an internal state of the preceding subnetwork, and a future setpoint for a corresponding future instance of time. Each of the second subnetworks outputs an individual prediction of each fault of a plurality of faults at the corresponding future instance of time.
机译:系统在一组未来的时间实例中评估机器运行中的多个故障。该系统使用神经网络,该神经网络包括第一子网络,该子网络对于每个未来的时间实例依次与第二子网络的序列连接,使得一个子网络的输出是随后子网络的输入。第一个子网接受当前的时间序列数据和机器的当前运行设定点。每个第二子网都接受先前子网的输出,先前子网的内部状态以及相应的未来时间实例的未来设定点。每个第二子网在相应的未来时间实例上输出多个故障中每个故障的单独预测。

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