MULTI-LOCATIONAL FORECAST MODELING IN BOTH TEMPORAL AND SPATIAL DIMENSIONS

    公开(公告)号:US20230073564A1

    公开(公告)日:2023-03-09

    申请号:US17458728

    申请日:2021-08-27

    IPC分类号: G06F30/20

    摘要: Temporal and spatially integrated forecast modeling includes generating a plurality of forecast models for a plurality of short-term to long-term time periods for a plurality of locations. Temporally integrating the plurality of forecast models sequentially over the plurality of time periods for the plurality of locations and spatially integrating the temporally integrated plurality of forecast models for each location hierarchically over the geographic areas. The forecast models are autoregressive distributed lag models with different explanatory variables for the short-term and long-term forecast models. The temporally integrating includes recursively integrating the plurality of forecast models over the time periods from the short-term to the long-term time periods and the spatially integrating includes recursively integrating the temporally integrated plurality of forecast models hierarchically from larger size geographic areas to smaller size geographic areas. The method includes optimizing the resultant spatially and temporally integrated forecast model based on a plurality of constraints.

    MODEL FIDELITY MONITORING AND REGENERATION FOR MANUFACTURING PROCESS DECISION SUPPORT

    公开(公告)号:US20220011760A1

    公开(公告)日:2022-01-13

    申请号:US16923148

    申请日:2020-07-08

    IPC分类号: G05B23/02 G05B13/04 G05B13/02

    摘要: Techniques for model fidelity monitoring and regeneration for manufacturing process decision support are described herein. Aspects of the invention include determining that an output of a regression model corresponding to a current time period of decision support for a manufacturing process is not within a predefined range of a historical process dataset, wherein the regression model was constructed based on the historical process dataset, and performing an accuracy and fidelity analysis on the regression model based on process data from the manufacturing process corresponding to a previous time period. Based on a result of the accuracy and fidelity analysis being below a threshold, a mismatch of the regression model as compared to the manufacturing process is determined. Based on determining the mismatch, a temporary regression model corresponding to the manufacturing process is generated, and decision support for the manufacturing process is performed based on the temporary regression model.

    Evaluating project maturity from data sources

    公开(公告)号:US10241786B2

    公开(公告)日:2019-03-26

    申请号:US15415943

    申请日:2017-01-26

    IPC分类号: G06F9/44 G06F8/77 G06Q10/00

    摘要: Techniques are provided for performing automated operations to determine maturity of a specified project. Information is received regarding each of a plurality of artifacts associated with the project, such as project documentation, source code repositories, and a tracked issue database for the project. A data sufficiency level associated with each provided artifact is determined, and each artifact is provided to one or more of multiple analysis engines. The analysis engines are executed to produce one or more weighted feature vectors for each of the artifacts associated with the specified project, and input to a prediction engine in order to provide a maturity rating for the project based on the weighted feature vectors.

    EQUIPMENT MAINTENANCE IN GEO-DISTRIBUTED EQUIPMENT

    公开(公告)号:US20220058590A1

    公开(公告)日:2022-02-24

    申请号:US16998486

    申请日:2020-08-20

    摘要: A computer-implemented method for maintaining equipment in a geo-distributed system includes receiving, by a processor, a selection of quantities to optimize when adjusting a maintenance schedule of the geo-distributed system that includes multiple pieces of equipment that are spread over a geographical region, and wherein the maintenance schedule identifies when a set of maintenance tasks are executed at a first equipment from the geo-distributed system over a predetermined duration. The method further includes generating, by the processor, a mixed-integer linear program for optimizing the maintenance schedule using a set of predetermined constraints. The method further includes executing, by the processor, the mixed-integer linear program via a mixed-integer linear program solver. The method further includes adjusting, by the processor, the maintenance schedule by selecting only a subset of the maintenance tasks.