Viable forecasting monthly weather data using time series methods
نویسندگان
چکیده
The main object of the research was to assess forecast values weather parameters by using three-time series methods such as Decomposition time series, Autoregressive (AR) model with seasonal dummies and moving average (ARMA) /Autoregressive Integrated (ARIMA) model. A recent phenomenon in changing has disturbed world general Pakistan particular. In due climate change, flood heat stroke have taken many lives. Stationarity measured through Augmented Dickey-Fuller test; results showed that some variables are I(0) I(1). reliability examined goodness fit test. For finding best model, performance measures various models: Root Mean Squire Error, Absolute Error Percentage were considered. which above statistics minimum chosen appropriate After analysis validation, it observed AR-model found be between three models. Meanwhile, forecasting for period Jan.2018 Dec.2018 made based on Given future results, temperature will normal at selected stations. wind rainfall also present. Overall, suggested obtained findings meteorological stations' might coming few months over there, no chance heatstroke expected. Future studies must carried out provide awareness well-being regarding ecological hazardous minimize their economic loss mass media.
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ژورنال
عنوان ژورنال: Ecological Questions
سال: 2022
ISSN: ['1644-7298', '2083-5469']
DOI: https://doi.org/10.12775/eq.2023.003