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Machine Learning and Artificial Intelligence for Agricultural Economics

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Machine Learning and Artificial Intelligence for Agricultural Economics Synopsis

This book discusses machine learning and artificial intelligence (AI) for agricultural economics. It is written with a view towards bringing the benefits of advanced analytics and prognostics capabilities to small scale farmers worldwide. This volume provides data science and software engineering teams with the skills and tools to fully utilize economic models to develop the software capabilities necessary for creating lifesaving applications. The book introduces essential agricultural economic concepts from the perspective of full-scale software development with the emphasis on creating niche blue ocean products. Chapters detail several agricultural economic and AI reference architectures with a focus on data integration, algorithm development, regression, prognostics model development and mathematical optimization. Upgrading traditional AI software development paradigms to function in dynamic agricultural and economic markets, this volume will be of great use to researchers and students in agricultural economics, data science, engineering, and machine learning as well as engineers and industry professionals in the public and private sectors.

About This Edition

ISBN: 9783030774875
Publication date:
Author: Chandrasekar Vuppalapati
Publisher: Springer Nature Switzerland AG
Format: Paperback
Pagination: 599 pages
Series: International Series in Operations Research & Management Science
Genres: Operational research
Agricultural science
Machine learning
Algorithms and data structures
Management decision making
Agribusiness and primary industries
Information theory