Agricultural commodity price forecasting represents a key concern for market participants.
We explore the usefulness of neural network modeling for forecasting problems in datasets …

The fluctuations of agricultural commodity prices have a great impact on people's daily lives
as well as the inputs and outputs of agricultural production. An accurate forecast of …

The recent extreme volatility in agriculture prices determines serious repercussions to
various stakeholders and levels in the food value chain, that is, producers, intermediaries …

Forecasting the price of agricultural produce helps grower decide planting, harvesting, and
trading time. Price forecasting of crops has garnered many researchers' attention, hence …

Purpose The purpose of this paper is to present a novel framework for strategic decision
making using Big Data Analytics (BDA) methodology. Design/methodology/approach In this …

A vast number of studies are devoted to the short-term forecasting of agricultural production
and market. However, those results are more helpful for market traders than producers and …

Background Grain commodities are important to people's daily lives and their fluctuations
can cause instability for households. Accurate prediction of grain prices can improve food …

Abstract The United Nations (UN) Food and Agriculture (FAO) estimates that farmers will
need to produce about 70% more food by 2050. To accommodate the growing demand, the …

This paper aimed to develop a data-based technological innovation framework focused on
the competitive intelligence process. Technological innovations increasingly transform the …

Aim: The aim of the study was to determine the trend of wheat prices using technical
analysis indicators. Methodology: Selected technical analysis indicators were used to …