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This paper tries to explore the situations in the business industry domain which concentrates on the analysis of seasonal time series data using Holt-Winters ...
Forecasting Industry Big Data with Holt Winter's Method from a Perspective of In-Memory Paradigm. Authors: Sudipto Shankar Dasgupta. Sudipto Shankar Dasgupta.
This paper tries to explore the situations in the business industry domain which concentrates on the analysis of seasonal time series data using ...
Industrial data in time series exhibit seasonal behavior like demand for materials for any Industry and this call for seasonal forecasting which is of ...
This paper tries to explore the situations in the business industry domain which con- centrates on the analysis of seasonal time series data using Holt-Winters ...
First a multilayer perceptron model for time series forecasting is proposed. Several learning rules used to adjust the ANN weights have been evaluated. Secondly ...
This article discusses two methods of dealing with demand variability in seasonal time series using artificial neural networks (ANN). First a multilayer ...
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Oct 22, 2024 · The research work focus on the analysis of seasonal time series data using additive and multiplicative seasonal model of Holt–winters method and forecast the ...
Oct 28, 2014 · Forecasting Industry Big Data with Holt Winter's Method from a Perspective of In-Memory Paradigm http://t.co/tK413tppDX #springerlink.
Jan 2, 2024 · This study predicted that the Holt-Winters and Prophet methods, both of which are based on historical data, would be useful for long-term load forecasting.