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公开(公告)号:US20230325743A1
公开(公告)日:2023-10-12
申请号:US18335570
申请日:2023-06-15
Applicant: Kinaxis Inc.
Inventor: Marcio OLIVEIRA ALMEIDA , Zhen LIN , Behrouz HAJI SOLEIMANI , Seyednaser NOURASHRAFEDDIN , Chantal BISSON-KROL
IPC: G06Q10/0631 , G06N5/048 , G06N20/00
CPC classification number: G06Q10/06315 , G06N5/048 , G06N20/00 , G06F16/285
Abstract: A method and system for a machine learning duster analysis of historical lead time data, which is augmented by one or more features. The data can also be divided into groups, based on time-density of the data, with clustering performed on each group. Furthermore, clustering can also be projected onto two dimensions. in addition, the historical lead time data is separated into a plurality of tolerance zones based on tolerance criteria. The clusters are separated in accordance with a tolerance zone of each group; and further separated according to one or more lead time identifiers to provide one or more separated clusters.
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公开(公告)号:US20250054001A1
公开(公告)日:2025-02-13
申请号:US18800753
申请日:2024-08-12
Applicant: Kinaxis Inc.
Inventor: Ali KHANAFER , Behrouz HAJI SOLEIMANI
IPC: G06Q30/0201 , G06N20/00
Abstract: Disclosed are systems and methods that relate to demand forecasting based on machine learning of historical data, while adjusting forecasts based real-time data.
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公开(公告)号:US20240112129A1
公开(公告)日:2024-04-04
申请号:US18538382
申请日:2023-12-13
Applicant: Kinaxis Inc.
Inventor: Phillip WILLIAMS , Zhen LIN , Behrouz HAJI SOLEIMANI , Seyednaser NOURASHRAFEDDIN , Chantal BISSON-KROL , Marcio OLIVEIRA ALMEIDA
IPC: G06Q10/083 , G06F18/2321 , G06N20/00
CPC classification number: G06Q10/0838 , G06F18/2321 , G06N20/00
Abstract: A dynamic supply chain planning system for analysis of historical lead time data that uses machine learning algorithms to forecast future lead times based on historical lead time data, weather data and financial data related to locations and dates within the supply chain.
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公开(公告)号:US20220335378A1
公开(公告)日:2022-10-20
申请号:US17740869
申请日:2022-05-10
Applicant: KINAXIS INC.
Inventor: Phillip WILLIAMS , Zhen LIN , Behrouz HAJI SOLEIMANI , Seyednaser NOURASHRAFEDDIN , Chantal BISSON-KROL , Marcio OLIVEIRA ALMEIDA
Abstract: A dynamic supply chain planning system for analysis of historical lead time data that uses machine learning algorithms to forecast future lead times based on historical lead time data, weather data and financial data related to locations and dates within the supply chain.
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