Machine Learning in Agriculture

filler

Title: Paperback
Price:
Sale price£42.50

Description

The amount of crops harvested varies every year due to changes in climate and other operational as well as economic factors. Predicting the amount of crops a land will produce will result in more efficient field operations and management. At a national level, crop yield prediction can help work towards achieving food security. This, at a global level, will serve as a step towards the UN Sustainable Development Goal of Zero Hunger. This research identifies the significant factors that affect the production of staple crops in regions with desert and semi-arid climate in Africa and predict their yield. Different techniques are experimented to create the model and Random Forest proves to be the most suitable for this problem.

Details

Publisher - Eliva Press LTD

Author(s) - Hames Sherif

Paperback

Published Date - July 27 2023

ISBN - 9789994988730

Dimensions - 22.9 x 15.2 x 0.3 cm

Page Count - 45

Payment & Security

American Express Apple Pay Diners Club Discover Maestro Mastercard Shop Pay Union Pay Visa

Your payment information is processed securely. We do not store credit card details nor have access to your credit card information.

You may also like

Recently viewed