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    • 1. 发明申请
    • METHOD AND SYSTEM FOR EXPLOITING INFORMATION FROM HETEROGENEOUS SOURCES
    • 从异质来源获取信息的方法和系统
    • US20090240481A1
    • 2009-09-24
    • US12398171
    • 2009-03-04
    • Hugh DURRANT-WHYTEFabio Tozeto RamosPeter James Hatherly
    • Hugh DURRANT-WHYTEFabio Tozeto RamosPeter James Hatherly
    • G06G7/48
    • G06Q10/06
    • A system and method are described for generating a model of an environment in which a plurality of equipment units (104) are deployed for the extraction of at least one resource from the environment. The system comprises a pre-extraction or in-ground modelling unit (204) configured to receive data from a first plurality of heterogeneous sensors in the environment and to fuse the data into a pre-extraction model descriptive of the environment and the at least one resource. An equipment modelling unit (208) is configured to receive equipment data relating to the plurality of equipment units operating in the environment and to combine the equipment data into an equipment model. A post-extraction or out-of-ground modelling unit (206) is configured to receive data from a second plurality of sensors and to fuse the data into a post-extraction model descriptive of material extracted from the environment, wherein at least one of the equipment units operates to extract the at least one resource from the environment. Information from at least one of the pre-extraction model, the equipment model and the post-extraction model is communicable to the equipment units for use in controlling operation of the equipment units in the environment. The environment may be a mine.
    • 描述了一种用于生成环境模型的系统和方法,其中多个设备单元(104)被部署用于从环境中提取至少一个资源。 该系统包括预提取或地面间建模单元(204),其被配置为从环境中的第一多个异构传感器接收数据,并将数据融合到描述环境的预提取模型中,并且至少一个 资源。 设备建模单元(208)被配置为接收与在环境中操作的多个设备单元有关的设备数据,并将设备数据组合成设备模型。 后提取或地面外建模单元(206)被配置为从第二多个传感器接收数据并且将数据融合到描述从环境提取的材料的后提取模型中,其中至少一个 设备单元操作以从环境中提取至少一个资源。 来自提取前模型,设备模型和提取后模型中的至少一个的信息可以传送到设备单元,以用于控制环境中的设备单元的操作。 环境可能是一个矿。
    • 4. 发明授权
    • Method and system for exploiting information from heterogeneous sources
    • 利用异构资源的信息的方法和系统
    • US08315838B2
    • 2012-11-20
    • US12398171
    • 2009-03-04
    • Hugh Durrant-WhyteFabio Tozeto RamosPeter James Hatherly
    • Hugh Durrant-WhyteFabio Tozeto RamosPeter James Hatherly
    • G06F17/50
    • G06Q10/06
    • A system and method are described for generating a model of an environment in which a plurality of equipment units are deployed for the extraction of at least one resource from the environment. The system comprises a pre-extraction modeling unit configured to receive data from a first plurality of heterogeneous sensors in the environment and to fuse the data into a pre-extraction model. An equipment modeling unit is configured to receive equipment data relating to the plurality of equipment units and to combine the equipment data into an equipment model. A post-extraction modeling unit is configured to receive data from a second plurality of sensors and to fuse the data into a post-extraction model. Information from the pre-extraction model, the equipment model and/or the post-extraction model is communicable to the equipment units for use in controlling operation of the equipment units in the environment.
    • 描述了一种用于生成环境模型的系统和方法,其中部署多个设备单元用于从环境中提取至少一个资源。 该系统包括预提取建模单元,其被配置为从环境中的第一多个异构传感器接收数据,并将数据融合到预提取模型中。 设备建模单元被配置为接收与多个设备单元相关的设备数据,并将设备数据组合成设备模型。 后提取建模单元被配置为从第二多个传感器接收数据并且将数据融合到后提取模型中。 来自提取前模型,设备模型和/或提取后模型的信息可以连接到设备单元,以用于控制环境中的设备单元的操作。
    • 9. 发明授权
    • Method and system of data modelling
    • 数据建模方法与系统
    • US08849622B2
    • 2014-09-30
    • US12650444
    • 2009-12-30
    • Arman MelkumyanFabio Tozeto Ramos
    • Arman MelkumyanFabio Tozeto Ramos
    • G06F17/10G06F7/60G06F17/18
    • G06F17/18
    • A system for large scale data modelling is described. The system includes at least one data measurement sensor (230) for generating measured data, a training processor (240) to determine optimized hyperparameter values in relation to a Gaussian process covariance function including a sparse covariance function that is smooth and diminishes to zero outside of a characteristic hyperparameter length. An evaluation processor (260) determines model data from the Gaussian process covariance function with optimised hyperparameter values and measured data. Also described is methods for modelling date, including a method using a Gaussian process including a sparse covariance function that diminishes to zero outside of a characteristic length, wherein the characteristic length is determined from the data to be modelled.
    • 描述了一种用于大规模数据建模的系统。 该系统包括用于产生测量数据的至少一个数据测量传感器(230),训练处理器(240),用于确定与高斯过程协方差函数相关的优化超参数值,所述高斯过程协方差函数包括平滑的稀疏协方差函数,并且在 特征超参数长度。 评估处理器(260)从具有优化的超参数值和测量数据的高斯过程协方差函数确定模型数据。 还描述了用于建模日期的方法,包括使用包括在特征长度之外减小到零的稀疏协方差函数的高斯过程的方法,其中根据要建模的数据确定特征长度。