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    System and Method For Creating Customized Model Ensembles On Demand
    5.
    发明申请
    System and Method For Creating Customized Model Ensembles On Demand 审中-公开
    根据需要创建定制模型集合的系统和方法

    公开(公告)号：US20140188768A1

    公开(公告)日：2014-07-03

    申请号：US13729720

    申请日：2012-12-28

    Applicant: GENERAL ELECTRIC COMPANY

    Inventor： Piero Patrone Bonissone ,  Neil Holger White Eklund ,  Feng Xue ,  Naresh Sundaram Iyer ,  Weizhong Yan

    IPC: G06N99/00

    CPC classification number: G06N20/00

    Abstract: A computer-implemented system for creating customized model ensembles on demand is provided. An input module is configured to receive a query. A selection module is configured to create a model ensemble by selecting a subset of models from a plurality of models, wherein selecting includes evaluating an aspect of applicability of the models with respect to answering the query. An application module is configured to apply the model ensemble to the query, thereby generating a set of individual results. A combination module is configured to combine the set of individual results into a combined result and output the combined result, wherein combining the set of individual results includes evaluating performance characteristics of the model ensemble relative to the query.

    Abstract translation: 提供了一种用于根据需要创建定制模型组合的计算机实现的系统。 输入模块被配置为接收查询。 选择模块被配置为通过从多个模型中选择模型的子集来创建模型集合，其中选择包括评估模型在回答查询时的适用性的一个方面。 应用模块被配置为将模型集合应用于查询，从而生成一组单独的结果。 组合模块被配置为将该组个体结果组合成一个组合结果并输出组合结果，其中组合该单独结果包括评估模型集合相对于该查询的性能特征。

    Computer-Implemented Methods and Systems for Determining Fleet Conditions and Operational Management Thereof
    6.
    发明申请
    Computer-Implemented Methods and Systems for Determining Fleet Conditions and Operational Management Thereof 有权
    计算机实施方法和系统，用于确定舰队条件和操作管理

    公开(公告)号：US20140188767A1

    公开(公告)日：2014-07-03

    申请号：US13728378

    申请日：2012-12-27

    Applicant: GENERAL ELECTRIC COMPANY

    Inventor： Naresh Sundaram Iyer ,  Anil Varma ,  James Kenneth Aragones ,  Weizhong Yan ,  Piero Patrone Bonissone ,  Feng Xue

    IPC: G06N99/00

    CPC classification number: G06N5/04 ,  G06N99/005 ,  G06Q10/0631 ,  G06Q10/087 ,  G07C5/008

    Abstract: A method for determining fleet conditions and operational management thereof, performed by a central system includes receiving fleet data from at least one distributed data repository. The fleet data is substantially representative of information associated with a fleet of physical assets. The method also includes processing the received fleet data for the fleet using at least one process of a plurality of processes. The plurality of processes assess the received fleet data into processed fleet data. The method additionally includes determining a fleet condition status using the processed fleet data and the at least one process of the plurality of processes. The method further includes generating a fleet response. The fleet response is substantially representative of a next operational step for the fleet of physical assets. The method also includes transmitting the fleet response to at least one of a plurality of fleet response recipients.

    Abstract translation: 由中央系统执行的用于确定车队状况和其操作管理的方法包括从至少一个分布式数据存储库接收车队数据。 船队数据实质上代表与实体资产船队相关联的信息。 该方法还包括使用多个过程的至少一个过程处理车队接收的车队数据。 多个过程将接收到的车队数据评估为处理后的车队数据。 该方法另外包括使用处理的车队数据和多个过程中的至少一个过程来确定车队状况状态。 该方法还包括产生车队响应。 舰队反应实质上代表了有形资产队伍的下一个操作步骤。 该方法还包括将车队响应发送到多个车队响应接收者中的至少一个。

    METHOD AND SYSTEM TO AUTOMATE THE MAINTENANCE OF DATA-DRIVEN ANALYTIC MODELS
    8.
    发明申请
    METHOD AND SYSTEM TO AUTOMATE THE MAINTENANCE OF DATA-DRIVEN ANALYTIC MODELS 有权
    自动维护数据驱动分析模型的方法和系统

    公开(公告)号：US20150355901A1

    公开(公告)日：2015-12-10

    申请号：US14297297

    申请日：2014-06-05

    Applicant: General Electric Company

    Inventor： Piero Patrone Bonissone ,  Naresh Sundaram Iyer ,  Feng Xue ,  Johan Michael Reimann ,  Paul Ardis

    IPC: G06F9/44

    CPC classification number: G06F8/70 ,  G06F8/355

    Abstract: A method, system, and non-transitory computer-readable medium, the method including determining automatically, by a processor, whether behavior for a model representing a plurality of entities and relationships therebetween deviates from a reference behavior for the model; determining, in response to the determination that the model does deviate from the reference behavior, at least one basis for the deviation; automatically forecasting an estimate of a remaining useful life for the model; and modifying the model to compensate for the deviation by at least one of modifying the model to accommodate the deviation and updating the model based on at least one new requirement.

    Abstract translation: 一种方法，系统和非暂时计算机可读介质，所述方法包括由处理器自动确定表示多个实体的模型的行为及其间的关系偏离所述模型的参考行为; 响应于确定所述模型偏离所述参考行为，确定所述偏差的至少一个基础; 自动预测模型的剩余使用寿命的估计值; 以及修改所述模型以通过至少一个修改所述模型以适应所述偏差并基于至少一个新要求来更新所述模型来补偿所述偏差。

    SYSTEM AND METHOD FOR AUTOMATIC MODEL IDENTIFICATION AND CREATION WITH HIGH SCALABILITY
    9.
    发明申请
    SYSTEM AND METHOD FOR AUTOMATIC MODEL IDENTIFICATION AND CREATION WITH HIGH SCALABILITY 审中-公开
    用于自动识别和创建具有高可缩放性的系统和方法

    公开(公告)号：US20140189702A1

    公开(公告)日：2014-07-03

    申请号：US13730392

    申请日：2012-12-28

    Applicant: GENERAL ELECTRIC COMPANY

    Inventor： Weizhong Yan ,  Anil Varma ,  Piero Patrone Bonissone ,  Naresh Sundaram Iyer ,  Feng Xue

    IPC: G06F9/50

    CPC classification number: G06F9/5027

    Abstract: A system includes a library of algorithms, and a request module configured to receive an execution request. The system also includes a job scheduler/optimizer module configured to select algorithms from the library and to create at least one execution job based on the algorithms and the execution request. The system further includes a resource module configured to determine execution computing resources from multiple computing sources, including internal computing resources and external computing resources. The system also includes an executor module configured to transmit an execution job to the computing resources.

    Abstract translation: 系统包括算法库和被配置为接收执行请求的请求模块。 该系统还包括作业调度器/优化器模块，配置为从库中选择算法，并且基于算法和执行请求创建至少一个执行作业。 该系统还包括资源模块，该资源模块被配置为从多个计算源确定执行计算资源，包括内部计算资源和外部计算资源。 该系统还包括被配置为将执行作业发送到计算资源的执行器模块。

    METHODS AND SYSTEMS FOR IDENTIFYING A PRECURSOR TO A FAILURE OF A COMPONENT IN A PHYSICAL SYSTEM
    10.
    发明申请
    METHODS AND SYSTEMS FOR IDENTIFYING A PRECURSOR TO A FAILURE OF A COMPONENT IN A PHYSICAL SYSTEM 审中-公开
    将前体识别为物理系统中组分失效的方法和系统

    公开(公告)号：US20140188777A1

    公开(公告)日：2014-07-03

    申请号：US13728572

    申请日：2012-12-27

    Applicant: GENERAL ELECTRIC COMPANY

    Inventor： Weizhong Yan ,  Anil Varma ,  Brock Estel Osborn ,  James Kenneth Aragones ,  Piero Patrone Bonissone ,  Naresh Sundaram Iyer ,  Hai Qiu

    IPC: G06N5/02

    CPC classification number: G06N5/04 ,  G06F11/008

    Abstract: A computer-implemented system for identifying a precursor to a failure of a particular type of component in a physical system is provided. The physical system includes sensors coupled to the physical system. The computer-implemented system includes a computing device, a database, a processor, and a memory device. The memory device includes historical data including sensor measurements. When instructions are executed by the processor, the processor receives the historical data from the memory device. The processor generates a predictive model. The predictive model uses, as inputs, sensor measurements in the historical data. The predictive model is able to differentiate between sensor measurements taken before the repair event and those taken after the repair event without a time of the repair event being an input to the predictive model. The processor designates at least one sensor measurements used as inputs to the predictive model as precursors to the failure of the component.

    Abstract translation: 提供了一种用于识别物理系统中特定类型的组件的故障的前兆的计算机实现的系统。 物理系统包括耦合到物理系统的传感器。 计算机实现的系统包括计算设备，数据库，处理器和存储设备。 存储器件包括包括传感器测量的历史数据。 当处理器执行指令时，处理器从存储器件接收历史数据。 处理器生成预测模型。 预测模型使用历史数据中的传感器测量作为输入。 该预测模型能够区分在修复事件之前进行的传感器测量与在修复事件之后进行的传感器测量之间，而没有修复事件的时间是预测模型的输入。 处理器指定用作预测模型的输入的至少一个传感器测量值作为组件故障的前兆。

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