Wavelet decomposition in signal processing has been widely used in the literature. The
popularity of machine learning (ML) algorithms is increasing day by day in agriculture, from …

Ensemble forecasts from multiple models have gained enormous popularity as it provides a
more efficient forecast as compared to the individual counterpart. The linear weighted …

Price volatility in agricultural commodities adds uncertainty for farmers, traders, and other
stakeholders in the agricultural supply chain. Sudden price changes can disrupt income …

Volatility is an important characteristic of time series. If the volatility of a series at any time
epoch is affected by its distant counterpart, then it is known as long memory in volatility. The …

Volatility is a matter of concern for time series modeling. It provides valuable insights into the
fluctuation and stability of concerning variables over time. Volatility patterns in historical data …

Time series modeling of the price of agricultural commodities has immense importance in
the Indian agricultural landscape. Volatility is an intrinsic property of time series. If positive …

Political and economic instability, armed conflicts, and weather abnormalities may introduce
a high degree of volatility to the refugee movement. Refugee movement volatility is said to …

Description The real-life time series data are hardly pure linear or nonlinear. Merging a
linear time series model like the autoregressive moving average (ARMA) model with a …