Parallel genetic algorithms for optimizing the SARIMA model for better forecasting of the NCDC weather data

Autoregressive Integrated Moving Average (ARIMA) and seasonal ARIMA (SARIMA) models are common techniques that are widely used in analysing and forecasting stationary and seasonal time series data. The three essential steps involved to construct ARIMA are identification, estimation, and checking the...

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主要な著者:	Mohammed Farsi, Doreswamy Hosahalli, B.R. Manjunatha, Ibrahim Gad, El-Sayed Atlam, Althobaiti Ahmed, Ghada Elmarhomy, Mahmoud Elmarhoumy, Osama A. Ghoneim
フォーマット:	Artigo
言語:	Inglês
出版事項:	Elsevier 2021-02-01
シリーズ:	Alexandria Engineering Journal
主題:	SARIMA algorithm NCDC dataset Weather analysis Data processing Genetic algorithms (GA) Parallel computing
オンライン･アクセス:	http://www.sciencedirect.com/science/article/pii/S1110016820305706
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