Arima-Based Forecast of Gross Fish Production in Sustainable Aquaculture

Forecasting gross fish production in sustainable aquaculture using the ARIMA (Autoregressive Integrated Moving Average) model has become an important analytical tool for production planning, risk management, and policy formulation in the fisheries sector. The ARIMA model is particularly effective for analyzing time series data, as it enables the identification of long-term trends and dynamic patterns in fish production volumes. Recent empirical studies demonstrate that ARIMA-based approaches provide reliable forecasts of aquaculture output across different time horizons. In particular, model-based projections indicate a steady growth trend in gross fish production over the medium and long term, reflecting the increasing role of innovative technologies and improved management practices in aquaculture. The strength of the ARIMA model lies in its ability to utilize historical production data to generate accurate forecasts of future output, which is especially relevant in regions where fish farming performance is affected by environmental conditions, feed efficiency, technological intensity, and market factors. The application of ARIMA forecasting allows fish producers and policymakers to anticipate production fluctuations, improve resource allocation, and support sustainable development objectives in aquaculture. Overall, the use of the ARIMA model in forecasting gross fish production contributes to a deeper understanding of production dynamics and provides a scientific basis for designing effective strategies to enhance the economic efficiency and sustainability of fish farming.