Background Price forecasting of perishable crop like vegetables has importance
implications to the farmers, traders as well as consumers. Timely and accurate forecast of …

Statistical tools for forecasting purpose started using smooth exponential methods in 1950s.
These methods were modified depending upon the trend followed in the data sets, based …

In this paper, stock price data has been predicted using several state-of-the-art
methodologies such as stochastic models, machine learning techniqus, and deep learning …

Objectives The forecasting of horticulture commodity prices, such as bananas, has wide-
ranging impacts on farmers, traders and end-users. The considerable volatility in …

Agricultural price forecasting, with its distinctive characteristics, remains a captivating field of
study. In countries like India, grappling with food security challenges, reliable and efficient …

The fractional integration is a generalization of integer integration, under which time-series
are usually presumed to be integrated of order zero or one. In this regard, the autoregressive …

Share of livestock sector especially dairy production in total gross domestic product (GDP)
has shown a continuous rise trend over the last 30 years. Autoregressive integrated moving …

The book is a unique collection of studies involving intelligent systems and applications of
artificial intelligence in the real world to provide solutions to most vexing problems. IntelliSys …

The study developed ARIMA forecasting model for brinjal prices for the markets of Eastern
Uttar Pradesh. It was observed that the ARIMA (1, 0, 1) with non-zero mean was suitable for …

Agricultural price forecasting has become a promising area of research in recent times.
ARIMA model has been most widely used technique during the last few decades for this …