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SYSTEMS AND METHODS FOR REAL-TIME DATA PROCESSING AND FOR EMERGENCY PLANNING

机译:用于实时数据处理和应急计划的系统和方法

摘要

Systems and methods are described herein for real-time data processing and for emergency planning. Scenario test data may be collected in real-time based on monitoring local or regional data to ascertain any anomaly phenomenon that may indicate an imminent danger or of concern. A computer-implemented method may include filtering a plurality of different test scenarios to identify a sub-set of test scenarios from the plurality of different test scenarios that may have similar behavior characteristics. A sub-set of test scenarios is provided to a trained neural network to identify one or more sub-set of test scenarios. The one or more identified sub-set of test scenarios may correspond to one or more anomaly test scenarios from the sub-set of test scenarios that is most likely to lead to an undesirable outcome. The neural network may be one of: a conventional neural network and a modular neural network.
机译:本文描述了系统和方法,用于实时数据处理和用于紧急计划。 可以基于监测本地或区域数据的实时收集方案测试数据,以确定任何可能表明迫在眉睫的危险或关注的任何异常现象。 计算机实现的方法可以包括过滤多个不同的测试场景,以从多个不同的测试场景识别可能具有类似行为特征的多个不同的测试场景的测试场景。 将一组测试场景提供给培训的神经网络,以识别一个或多个子集的测试场景。 测试场景的一个或多个已识别的子集可以对应于来自最有可能导致不期望的结果的测试场景的一个或多个异常测试场景。 神经网络可以是:传统的神经网络和模块化神经网络之一。

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