Scheduling business process
    1.
    发明授权

    公开(公告)号:US11188882B2

    公开(公告)日:2021-11-30

    申请号:US16287279

    申请日:2019-02-27

    IPC分类号: G06Q10/10 G06Q10/06

    摘要: A system and method for scheduling a business process including tasks, comprises a calculation unit, a determination unit, and a decision unit. The calculation unit is configured to calculate an estimated processing time required to execute the tasks. The determination unit is configured to calculate an estimated end time of a route including the tasks on the basis of the estimated processing time and schedule of a user to execute the tasks, and determine whether to apply speculative execution to the business process on the basis of the estimated end time. The decision unit is configured to decide to speculatively execute a task out of the tasks in the business process. The decision is made with reference to a remaining period for executing the task. The remaining period is calculated on the basis of a predicted execution timing of each task and a deadline of the business process.

    EFFECTIVENESS OF SERVICE COMPLEXITY CONFIGURATIONS IN TOP-DOWN COMPLEX SERVICES DESIGN

    公开(公告)号:US20170178168A1

    公开(公告)日:2017-06-22

    申请号:US14977383

    申请日:2015-12-21

    IPC分类号: G06Q30/02 G06F17/30

    CPC分类号: G06Q30/0206 G06Q30/0202

    摘要: One embodiment provides a method comprising receiving historic peer deals relating to at least one service, and a baseline and cost percentage estimation for each service. Historic peer cost data for each service is clustered to form at least one cluster. Each cluster includes similar unit costs, and has an assigned label. A classification model is trained based on each baseline received, each cost percentage estimation received, and each assigned label. For each assigned label, a corresponding probability distribution is computed based on the classification model. For each service of a new client solution, an assigned label for the service is predicted based on the classification model, and, based on a probability distribution corresponding to the assigned label predicted, transforming an initial range of historic peer cost data relating to the service into a narrower range for use in estimating a cost of the service with improved accuracy.

    Preemptive mitigation of collision risk

    公开(公告)号:US11279344B2

    公开(公告)日:2022-03-22

    申请号:US16205718

    申请日:2018-11-30

    摘要: A method, computer system, and a computer program product for preemptive collision mitigation is provided. The present invention may include calculating a future position of a first vehicle based on carprobe data from a first vehicle, wherein the carprobe data contains neural data of an operator of the first vehicle. The present invention may also include calculating a distance between the future position of the first vehicle and a future position of a second vehicle. The present invention may then include determining the calculated distance between the future position of the first vehicle and the future position of the second vehicle is below a threshold distance.

    Effectiveness of service complexity configurations in top-down complex services design

    公开(公告)号:US11120460B2

    公开(公告)日:2021-09-14

    申请号:US14977383

    申请日:2015-12-21

    IPC分类号: G06Q30/02

    摘要: One embodiment provides a method comprising receiving historic peer deals relating to at least one service, and a baseline and cost percentage estimation for each service. Historic peer cost data for each service is clustered to form at least one cluster. Each cluster includes similar unit costs, and has an assigned label. A classification model is trained based on each baseline received, each cost percentage estimation received, and each assigned label. For each assigned label, a corresponding probability distribution is computed based on the classification model. For each service of a new client solution, an assigned label for the service is predicted based on the classification model, and, based on a probability distribution corresponding to the assigned label predicted, transforming an initial range of historic peer cost data relating to the service into a narrower range for use in estimating a cost of the service with improved accuracy.