Abstract
A novel methodology is designed to forecast ink usage for following 2 months from multivariable time
series data. Proposed approach also incorporates the impact of unprecedented events such as
COVID pandemic. It uses Deep Learning Encoder Decoder model for identifying the seasonality,
trend and sudden changepoints in multivariate time series.
Creative Commons License
This work is licensed under a Creative Commons Attribution-Share Alike 4.0 License.
Recommended Citation
INC, HP, "INK CONSUMPTION FORECASTING DURING PANDEMIC USING DEEP LEARNING APPROACH", Technical Disclosure Commons, (February 24, 2021)
https://www.tdcommons.org/dpubs_series/4101
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