SARIMA
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Time Series Forecasting of Electricity Consumption: A Comparative Analysis of ARIMA and SARIMA Models
Abstract: Accurate electricity demand forecasting plays a vital role in energy planning, efficient power system operation, and sustainable resource management. This study conducts a comparative evaluation of the Autoregressive Integrated Moving Average (ARIMA) and Seasonal Autoregressive Integrated Moving Average (SARIMA) models using ten years of monthly electricity consumption data collected from a national electricity regulatory authority. The performance of both models is assessed using forecasting accuracy metrics, including Mean Absolute Error …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 2, 2026 · pp. 43–53 Read article
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Study of Various Forecasting Models for Time Series Data Using Stochastic Processes
Abstract: The data which is in time stamped format is called as time series data. The time series data is everywhere, for example, weather data, stock market data, health care data, sensor data, network data, sales data and many more. Time series have various components due to which the time series data became complex. Trend, seasonality, cyclical, and irregularities, these are different components. As everyone is interested to know about future. …
Published in Journal of Computer Technology & Applications · Vol. 12, Issue 2, 2021 · pp. 26–32 Read article