Trends in marine fish production in Tamil Nadu using regression and autoregressive integrated moving average (ARIMA) model

ARIMA (autoregressive integrated moving average) is a combination of autoregressive and moving average models and the prediction value is determined through the analysis

The linear models, ARIMA and PSOARIMA, show poor performance with a relatively large error values in comparison to nonlinear model, PSOSVR and hybrid models.. On the other hand,

The total annual catch of demersal and pelagic fishery resources in the marine fish landings of Puducherry and their percentage composition are given in Table 17. During 1990s

The performance of Autoregressive Moving Average and Multiple Linear Regression Models in pre- dicting minimum and maximum temperatures of Ogun State is herein

The hybrid QRNN method has following steps, (1) implementing time series regression modeling, (2) performing ARIMA modeling using Box-Jenkins procedure on residual

The data selected for this study are started from January 2013 until October 2017.We performed the forecasting approach using autoregressive integrated moving average