Recurrent neural network architecture for forecasting banana prices in Gujarat, India.

ABSTRACT:

Objectives

The forecasting of horticulture commodity prices, such as bananas, has wide-ranging impacts on farmers, traders and end-users. The considerable volatility in horticultural commodities pricing estimates has allowed farmers to exploit various local marketplaces for profitable sales of their farm produce. Despite the demonstrated efficacy of machine learning models as a suitable substitute for conventional statistical approaches, their application for price forecasting in the context of Indian horticulture remains an area of contention. Past attempts to forecast agricultural commodity prices have relied on a wide variety of statistical models, each of which comes with its own set of limitations.

Methods

Although machine learning models have emerged as formidable alte

SUBMITTER: Kumari P 

PROVIDER: S-EPMC10270605 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature