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- Includes supplementary material: sn.pub/extras
Part of the book series: SpringerBriefs in Applied Sciences and Technology (BRIEFSAPPLSCIENCES)
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Keywords
- Principal Component Regression (PCR)
- Multiple Linear Regression Models (MLR)
- Principal Component Analysis (PCA)
- Climate change for crops
- Statistical downscaling methods
- Multi-co-linearity problem
- Climatological parameters
- Crop yield Estimation Models
- Performance Indices
- Water resource management
- climate change impacts
- water policy
Table of contents (7 chapters)
Authors and Affiliations
About the authors
Dr. T. M. V. Suryanarayana is serving as Associate Professor and recognized Ph.D. Guide in Water Resources Engineering and Management Institute, The M. S. University of Baroda. He is Executive Committee Member of Indian Water Resources Society, Secretary and Treasurer of Gujarat Chapter of Association of Hydrologists of India and Joint Secretary of Indian Society of Geomatics_Vadodara Chapter. He has 74 research papers published in various International/National Journals/ Seminars/ Conferences/ Symposiums.
Mr. P. B. Mistry has obtained B.E. (Civil-Irrigation
Water Management) and M.E. (Civil) in Water Resources Engineering from The M.S.
University of Baroda and is presently working as Assistant Professor in Parul
University, Vadodara. He is a life member of Indian Society of Geomatics and
Indian Society for Hydraulics.
Bibliographic Information
Book Title: Principal Component Regression for Crop Yield Estimation
Authors: T.M.V Suryanarayana, P. B Mistry
Series Title: SpringerBriefs in Applied Sciences and Technology
DOI: https://doi.org/10.1007/978-981-10-0663-0
Publisher: Springer Singapore
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer International Publishing Switzerland 2016
Softcover ISBN: 978-981-10-0662-3Published: 30 March 2016
eBook ISBN: 978-981-10-0663-0Published: 21 March 2016
Series ISSN: 2191-530X
Series E-ISSN: 2191-5318
Edition Number: 1
Number of Pages: XVII, 67
Number of Illustrations: 12 illustrations in colour
Topics: Mathematical and Computational Engineering, Climate Change/Climate Change Impacts, Statistical Theory and Methods, Math. Appl. in Environmental Science, Agriculture, Water Policy/Water Governance/Water Management