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    CASH DEMAND PREDICTION SYSTEM, CASH DEMAND PREDICTION METHOD, AND CASH DEMAND PREDICTION PROGRAM
    1.
    发明申请
    CASH DEMAND PREDICTION SYSTEM, CASH DEMAND PREDICTION METHOD, AND CASH DEMAND PREDICTION PROGRAM 有权

    公开(公告)号：US20210158380A1

    公开(公告)日：2021-05-27

    申请号：US16640839

    申请日：2018-06-27

    Applicant: NEC CORPORATION

    Inventor： Takashi TOUKAIRIN ,  Yousuke MOTOHASHI ,  Keiji KANDA ,  Akira TANIMOTO

    IPC: G06Q30/02 ,  G06N20/00 ,  G06N5/02

    Abstract: A predicting data generation unit 91 generates, on the basis of a prediction day, predicting data having added thereto a value of an explanatory variable indicating whether the day corresponds to a date predetermined as a day on which cash transfer will take place. A prediction device 92 predicts cash demand by applying the predicting data to a learned model, the learned model having prediction formulae determined depending on a value of an explanatory variable. The prediction device 92, in accordance with the value of the explanatory variable included in the predicting data, selects a prediction formula for use in the prediction from among the plurality of prediction formulae indicated by the learned model, and applies the predicting data to the selected prediction formula to predict the cash demand.

    ACCURACY-ESTIMATING-MODEL GENERATING SYSTEM AND ACCURACY ESTIMATING SYSTEM
    3.
    发明申请
    ACCURACY-ESTIMATING-MODEL GENERATING SYSTEM AND ACCURACY ESTIMATING SYSTEM 审中-公开

    公开(公告)号：US20180075360A1

    公开(公告)日：2018-03-15

    申请号：US15560085

    申请日：2016-03-08

    Applicant: NEC CORPORATION

    Inventor： Akira TANIMOTO ,  Junpei KOMIYAMA ,  Yousuke MOTOHASHI ,  Ryohei FUJIMAKI ,  Yasuhiro SOGAWA

    IPC: G06N5/04 ,  G06N99/00

    CPC classification number: G06N5/048 ,  G06N20/00

    Abstract: An accuracy estimation unit 91 estimates accuracy of a predictive model using an accuracy estimating model that is learned using, as an explanatory variable, all or part of one or more contexts each indicating a feature value representing an operation status of the predictive model at a first point of interest that is a past point in time of interest a learning period of the predictive model, and a parameter used to learn the predictive model and, as a response variable, an accuracy index in a period after the first point of interest. The accuracy estimation unit 91 calculates the context at a second point of interest that is a point in time after the first point of interest, and applies the calculated context to the accuracy estimating model to estimate the accuracy from the second point of interest onward.

    LEARNING DEVICE, LEARNING METHOD, AND RECORDING MEDIUM
    6.
    发明公开
    LEARNING DEVICE, LEARNING METHOD, AND RECORDING MEDIUM 审中-公开

    公开(公告)号：US20240119296A1

    公开(公告)日：2024-04-11

    申请号：US18276290

    申请日：2021-06-07

    Applicant: NEC Corporation

    Inventor： Akira TANIMOTO ,  Tomoya SAKAI ,  Takashi TAKENOUCHI ,  Hisashi KASHIMA

    IPC: G06N3/09

    CPC classification number: G06N3/09

    Abstract: A learning device calculates an estimation target item reference value according to a fixed value of each estimation target object. The learning device acquires learning data that includes the fixed value of each estimation target object, a variable item value, and an estimation target item value according to the fixed value and the variable item value. The learning device trains, using the learning data and an evaluation function, a model that outputs an estimated value of the estimation target item value in response to input of the fixed value of each estimation target object and the variable item value.

    MAINTENANCE RANGE OPTIMIZATION APPARATUS, MAINTENANCE RANGE OPTIMIZATION METHOD, AND COMPUTER-READABLE RECORDING MEDIUM
    7.
    发明申请
    MAINTENANCE RANGE OPTIMIZATION APPARATUS, MAINTENANCE RANGE OPTIMIZATION METHOD, AND COMPUTER-READABLE RECORDING MEDIUM 审中-公开

    公开(公告)号：US20200302347A1

    公开(公告)日：2020-09-24

    申请号：US16645228

    申请日：2018-09-07

    Applicant: NEC CORPORATION

    Inventor： Akira TANIMOTO

    IPC: G06Q10/04 ,  G06N20/00 ,  G06Q50/26

    Abstract: A maintenance range optimization apparatus 10 optimizes a range of maintenance on an object that requires maintenance at a plurality of places. The maintenance range optimization apparatus 10 includes a learning processing unit 20 that executes machine learning, using, as learning data, information from when maintenance was previously executed, including a pre-maintenance state, a maintenance cost and a movement cost of a place subjected to maintenance, and constructs a model indicating a relationship between the range of maintenance and an overall cost incurred in maintenance, and a maintenance range setting unit 30 that sets the range of maintenance using the model.

    LEARNING DEVICE, LEARNING METHOD AND RECORDING MEDIUM
    9.
    发明公开
    LEARNING DEVICE, LEARNING METHOD AND RECORDING MEDIUM 审中-公开

    公开(公告)号：US20240177060A1

    公开(公告)日：2024-05-30

    申请号：US18389273

    申请日：2023-11-14

    Applicant: NEC Corporation

    Inventor： Akira TANIMOTO

    IPC: G06N20/00

    CPC classification number: G06N20/00

    Abstract: There is proposed a technique of artificial intelligence (AI) which learns a model for causal inference by using an appropriate loss function. In a learning device, the acquisition means acquires learning data including an explanatory variable, an action, and information of outcome of the action. The learning means learns a model for performing causal inference, using the learning data, based on a loss function partially including a nuisance model which is an estimation object not necessary as a final output. The loss function is defined to pessimistically estimate a loss with respect to uncertainty of the nuisance model by using a worst value within a range in which the nuisance model is more certain than a predetermined value.

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