PROFIT PREDICTION USING TIME SERIES FORECASTING MODELS
Alt Text: Profit Prediction Using Time Series Forecasting Models
Title: Profit Prediction Using Time Series Forecasting Models
Caption: Comparing ARIMA, SARIMA, LSTM, and GRU for profit forecasting in business applications.
Description: This study evaluates four widely used time series forecasting models—ARIMA, SARIMA, LSTM, and GRU—to predict profit trends in business environments. By analyzing revenue generation and cost management patterns, the research determines the most effective model for accurate future predictions.
Keywords: Profit Prediction, Time Series Forecasting, ARIMA, LSTM, Business Intelligence
International Journal of Engineering and Techniques – Volume 10 Issue 3, June 2024
Mohammad Sainiya Khatun1, Mohammed Juveria Tharannum2
1UG Student, Department of Computer Science & Engineering, Geethanjali Institute of Science and Technology, Gangavaram, Andhra Pradesh, India.
2UG Student, Department of Computer Science & Engineering, Geethanjali Institute of Science and Technology, Gangavaram, Andhra Pradesh, India.
Abstract
Time series forecasting is a fundamental tool in various domains, enabling businesses to anticipate future trends and make informed decisions. This research conducts a comparative analysis of four widely used forecasting models—ARIMA, SARIMA, LSTM, and GRU—to predict profit in business contexts. Profit analysis provides insights into revenue generation, cost management, and overall financial performance. The study evaluates each model’s effectiveness in forecasting profit trends and variability and identifies the most suitable model for future predictions.
Keywords
Profit Prediction, Time Series Forecasting, ARIMA, LSTM, Business Intelligence
How to Cite
Khatun, M.S., Tharannum, M.J., “Profit Prediction Using Time Series Forecasting Models,” International Journal of Engineering and Techniques, Volume 10, Issue 3, June 2024. ISSN 2395-1303
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