Author(s): Neelam Chouksey, GP Painkra, KL Painkra and PK Bhagat

Abstract: Historical data has been leveraged to forecast honey bee population dynamics in the research paper. The study employs the Autoregressive Integrated Moving Average (ARIMA) methodology to predict honey bee population trends using time-based data from the Surguja district of Chhattisgarh. A comparative analysis of various fitted models is conducted, with a focus on assessing their performance through Mean Absolute Percentage Error (MAPE) and Root Mean Squared Error (RMSE). The findings indicate that the ARIMA (2,0,2) (0,0,2) model outperforms other models in terms of RMSE for forecasting honey bee population. Our approach involves meticulous scrutiny of the time series data, accompanied by a rigorous process of model identification and parameter estimation. This comprehensive methodology establishes a sturdy framework for generating precise predictions. The ramifications of our study are pertinent to enhancing informed decision-making within honey production management strategies.

Pages: 166-169 | Views: 197 | Downloads: 6

Download Full Article: Click Here