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Grant Award View - GA28911-V4
Efficient and effective analytics for real-world time series forecasting
GA ID:
GA28911-V4
Agency:
Australian Research Council
Approval Date:
27-Nov-2018
Variation Publish Date:
29-Apr-2022
Variation Date:
26-Apr-2022
Category:
Science, Technology, Engineering and Mathematics (STEM) Research
Grant Term:
18-Feb-2019 to 31-Dec-2022
Value (AUD):
$377,829.00
(GST inclusive where applicable)
Varies:
GA28911
- Efficient and effective analytics for real-world time series forecasting
One-off/Ad hoc:
No
Aggregate Grant Award:
No
PBS Program Name:
ARC 18/19 Discovery
Grant Program:
Discovery Early Career Researcher Award
Grant Activity:
Efficient and effective analytics for real-world time series forecasting
Purpose:
This project aims to create efficient, effective techniques that provide accurate forecasts for heterogeneous sets of time series of varying sizes. Exploiting similarities between time series means using many related series, not larger series when building forecasts. The expected outcomes should be innovative methods that improve accuracy and allow forecasting with shorter time series. The project addresses the need to exploit properties of big data accurately in a short time frame, which is transforming many industries. This should enable more accurate and reliable forecasts across industries as diverse as retail, food manufacturing, transport, mining, tourism, energy, and technology.
GO ID:
GO Title:
Discovery Early Career Researcher Award commencing in 2019
Internal Reference ID:
DE19 Round 1
Selection Process:
Targeted or Restricted Competitive
Confidentiality - Contract:
No
Confidentiality - Outputs:
No
Grant Recipient Details
Recipient Name:
Monash University
Recipient ABN:
12 377 614 012
Grant Recipient Location
Suburb:
MULGRAVE
Town/City:
MULGRAVE
Postcode:
3170
State/Territory:
VIC
Country:
AUSTRALIA
Grant Delivery Location
State/Territory:
VIC
Postcode:
3170
Country:
AUSTRALIA