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Machine Learning and Artificial Intelligence for Agricultural Economics = Prognostic Data Analytics to Serve Small Scale Farmers Worldwide /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Machine Learning and Artificial Intelligence for Agricultural Economics/ by Chandrasekar Vuppalapati.
其他題名:	Prognostic Data Analytics to Serve Small Scale Farmers Worldwide /
作者:	Vuppalapati, Chandrasekar.
面頁冊數:	XIX, 599 p. 317 illus., 286 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Operations Research, Management Science. -
電子資源:	https://doi.org/10.1007/978-3-030-77485-1
ISBN:	9783030774851

Machine Learning and Artificial Intelligence for Agricultural Economics = Prognostic Data Analytics to Serve Small Scale Farmers Worldwide /
Vuppalapati, Chandrasekar.

Machine Learning and Artificial Intelligence for Agricultural EconomicsPrognostic Data Analytics to Serve Small Scale Farmers Worldwide /[electronic resource] :by Chandrasekar Vuppalapati. - 1st ed. 2021. - XIX, 599 p. 317 illus., 286 illus. in color.online resource. - International Series in Operations Research & Management Science,3142214-7934 ;. - International Series in Operations Research & Management Science,227.

1. Introduction -- 2. Data Engineering and Exploratory Data Analysis Techniques -- 3. Agricultural Economy and ML Models -- 4. Commodity Markets - Machine Learning Techniques -- 5. Weather Patterns and Machine Learning -- 6. Agriculture Employment and the Role of AI in improving Productivity -- 7. Role of Government and the AI Readiness -- 8. Future.

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.

ISBN: 9783030774851

Standard No.: 10.1007/978-3-030-77485-1doiSubjects--Topical Terms:

785065
Operations Research, Management Science.

LC Class. No.: HD30.23

Dewey Class. No.: 658.40301

Machine Learning and Artificial Intelligence for Agricultural Economics = Prognostic Data Analytics to Serve Small Scale Farmers Worldwide /
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