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Winters'-Triple Seasonality model should be used in most cases where the coefficient of variance is of the demand data is large. The exponential smoothing with ...
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 ...
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 ...
Feb 10, 2024 · The Holt-Winters' Method is an extension of the simple exponential smoothing method, designed to handle time series data with trends and seasonality.
Oct 28, 2014 · Forecasting Industry Big Data with Holt Winter's Method from a Perspective of In-Memory Paradigm http://t.co/tK413tppDX #springerlink.