Time-Series Prediction Apparatus and Time-Series Prediction Method

    公开(公告)号:US20170300819A1

    公开(公告)日:2017-10-19

    申请号:US15513749

    申请日:2014-10-21

    Applicant: Hitachi, Ltd.

    CPC classification number: G06N5/04 G06F17/18 G06N20/00

    Abstract: A time-series prediction apparatus 10, which is an information processing apparatus that predicts transition of time-series data on a matter, calculates a relevance level which is an index of strength of a causal relation between a plurality of matters including a prediction target matter, based on time-series data relevant to each of the matters and on time-series data relevant to the causal relation between the matters, and predicts transition of the time-series data relevant to the matter based on the calculated relevance level. The time-series prediction apparatus 10 calculates the relevance level based on collocation frequency of terms relevant to the respective matters in the time-series data relevant to the causal relation between the matters. The time-series prediction apparatus 10 builds multiple prediction models for predicting the transition of the time-series data relevant to the prediction target matter based on time-series data relevant to a matter which is in a causal relation with the prediction target matter, and integrates prediction results of the respective prediction models while weighing each of the prediction models according to the relevance level.

    CALCULATING MACHINE, PREDICTION METHOD, AND PREDICTION PROGRAM
    3.
    发明申请
    CALCULATING MACHINE, PREDICTION METHOD, AND PREDICTION PROGRAM 审中-公开
    计算机,预测方法和预测方案

    公开(公告)号:US20140351008A1

    公开(公告)日:2014-11-27

    申请号:US14281266

    申请日:2014-05-19

    Applicant: Hitachi, Ltd.

    CPC classification number: G06Q30/0202 G06Q50/01

    Abstract: A calculating machine stores intermediate data generated for each product based on social media data including statements on a plurality of products. The intermediate data about each of the products includes at least a frequency of statements on each of the products for a predetermined period of time. The products include a first product that is not displayed for provision to a consumer at a present time, or at least a second product that has been displayed for provision at the present time. The calculating machine stores sales amount data indicating a sales amount of the second product, and calculates a social media correlation degree indicating a correlation between the intermediate data about the first product and the intermediate data about the second product to predict a sales amount of the first product based on the calculated social media correlation degree and the sales amount data about the second product.

    Abstract translation: 计算机基于包括关于多个产品上的语句的社交媒体数据来存储为每个产品生成的中间数据。 关于每个产品的中间数据在预定时间段内至少包括每个产品上的语句的频率。 这些产品包括当前不向消费者提供的第一个产品,或至少第二个产品,目前已被显示供用户使用。 计算机存储指示第二产品的销售量的销售量数据,并且计算指示关于第一产品的中间数据与关于第二产品的中间数据之间的相关性的社交媒体相关度,以预测第一产品的销售量 产品基于计算的社交媒体相关度和关于第二产品的销售量数据。

    TRANSPORTATION SERVICE PLANNING SYSTEM AND TRANSPORTATION SERVICE PLANNING METHOD

    公开(公告)号:US20210407021A1

    公开(公告)日:2021-12-30

    申请号:US17317995

    申请日:2021-05-12

    Applicant: Hitachi, Ltd.

    Abstract: Provided is a transportation service planning system including an operation unit and a storage unit. The storage unit stores an evaluation index designated for each of transportation systems, a creation condition of a service plan for each of the transportation systems, and a service simulation condition for each of the transportation systems. The operation unit creates a service plan for each of the transportation systems on the basis of the creation condition of the service plan, simulates a service of each of the transportation systems on the basis of the service plan and the simulation condition, calculates the evaluation index designated for each of the transportation systems on the basis of the simulation results, outputs the service plan if all of the evaluation indices satisfy a prescribed standard, and revises the service plan if at least one of the evaluation indices does not satisfy the prescribed standard.

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