Suhail Ashraf
Dados Biográficos
| ID | 7989367 |
|---|---|
| NOME | Suhail Ashraf |
| PRENOMES | Suhail |
| SOBRENOME | Ashraf |
| ASSINATURA | ASHRAF S |
| ORCID | 0000-0002-5851-3832 |
| VERIFICADO | Sim |
| TOTAL DE OBRAS | 1 |
| TOTAL DE CITAÇÕES | 0 |
| OBRAS COMO AUTOR | 1 |
| OBRAS COMO EDITOR | 0 |
| PRIMEIRO ANO DE PUBLICAÇÃO | 2024 |
| ANO MAIS RECENTE DE PUBLICAÇÃO | 2024 |
| ÍNDICE H | 0 |
Weather Forecasting
Time series is a statistical tool that is used for predicting future trends based on previous trends. In this study, forecasting of three weather stations of the UK presented. For that purpose, several methods are applied to the weather station data and the best fitting model is chosen for future forecasting. For the stationarity, informal (ACF and PACF) and formal (ADF) methods were presented. A well-known technique, Box-Jenkins (ARIMA), has bee…
Sem obras proeminentes nesta página.
Weather Forecasting
Time series is a statistical tool that is used for predicting future trends based on previous trends. In this study, forecasting of three weather stations of the UK presented. For that purpose, several methods are applied to the weather station data and the best fitting model is chosen for future forecasting. For the stationarity, informal (ACF and PACF) and formal (ADF) methods were presented. A well-known technique, Box-Jenkins (ARIMA), has bee…
Autocorrelation (1 obra) · Autoregressive integrated moving average (1 obra) · Box–Jenkins (1 obra) · Forecasting Techniques and Applications (1 obra) · Hydrological Forecasting Using AI (1 obra) · Moving average (1 obra) · Partial autocorrelation function (1 obra) · Series (stratigraphy (1 obra) · Statistical software (1 obra) · Stock Market Forecasting Methods (1 obra)