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:
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:
A system for determining anomaly conditions within a fleet of physical assets includes a central system having at least one computing device, the computing device including a processor and a memory device coupled to the processor and a database associated with the central system. The system includes a plurality of databases and a plurality of client devices associated with the fleet of physical assets. The system is configured to receive a first set of fleet data. The system is further configured to generate one or more computer-executable steps for detection of predicted anomalies. The system is configured to receive a first set of fleet asset data. The system is configured to detect at least one physical asset from the fleet of physical assets predicted to have at least one anomaly using the one or more computer-executable steps for detection of predicted anomalies and the first set of fleet asset data.
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:
A method for analyzing data is disclosed that includes receiving an analysis request to analyze selected data corresponding to one or more monitored assets, wherein the analysis request includes one or more parameters corresponding to performance categories of computing resources for processing the analysis request, the performance categories include at least one of a time for processing the analysis request or a cost for processing the analysis request; determining a computing resource allocation plan for processing the analysis request based on the one or more parameters; and processing the analysis request using the determined computing resource allocation plan to provide analysis results. Also disclosed is an analytic router that includes a mapper, an estimator, an optimizer, and a resource provisioner.
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:
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.