公开(公告)号：US20240119470A1

公开(公告)日：2024-04-11

申请号：US17955053

申请日：2022-09-28

Applicant: Panasonic Intellectual Property Management Co., Ltd.

Inventor： Debdeep PAUL ,  Chandra Suwandi Wijaya ,  Yizhou Huang ,  Khai Jun Kek ,  Koji Miura

IPC: G06Q30/02

CPC classification number: G06Q30/0202

Abstract: According to an embodiment, a method for generating a forecast of a timeseries is disclosed. The method comprises receiving a set of features comprising data and timeseries to be used by each of a plurality of prediction models for generating the forecast. Further, the method comprises generating using the set of features, a plurality of forecast results based on an ensemble of the plurality of prediction models. Furthermore, the method comprises optimizing the plurality of forecast results associated with a respective forecast module. Additionally, the method comprises probabilistically combining the outputs of the plurality of optimization modules. Moreover, the method comprises outputting a final forecast based on the combination of the at least two forecast results.

公开(公告)号：US20220058669A1

公开(公告)日：2022-02-24

申请号：US17001025

申请日：2020-08-24

Applicant: PANASONIC INTELLECTUAL PROPERTY MANAGEMENT CO., LTD.

Inventor： Yongning Yin ,  Debdeep Paul ,  Yizhou Huang ,  Khai Jun Kek

IPC: G06Q30/02 ,  G06N20/00

Abstract: Method and system is disclosed for forecasting demand with respect to an entity. The method comprises receiving a plurality of input data-sets associated with time-series data, wherein each of said data-sets refers a time-based variation of one or more variables in accordance with a designated time-interval. At least one transformation-result is generated by transforming time-intervals of at least one input dataset based on a plurality of time interval transformation models. A plurality of first intermediate forecast results are predicted based on a plurality of demand forecasting models from the at-least one transformation result. An aggregated result is generated from the plurality of the first intermediate forecast results through an ensemble-model to thereby render said aggregated result as a final prediction result.