Principal Component Regression for Crop Yield Estimation / SpringerBriefs in Applied Sciences and Technology (PDF)
(Sprache: Englisch)
This book highlights the estimation of crop yield in Central
Gujarat, especially with regard to the development of Multiple Regression
Models and Principal Component Regression (PCR) models using climatological
parameters as independent variables and...
Gujarat, especially with regard to the development of Multiple Regression
Models and Principal Component Regression (PCR) models using climatological
parameters as independent variables and...
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Produktinformationen zu „Principal Component Regression for Crop Yield Estimation / SpringerBriefs in Applied Sciences and Technology (PDF)“
This book highlights the estimation of crop yield in Central
Gujarat, especially with regard to the development of Multiple Regression
Models and Principal Component Regression (PCR) models using climatological
parameters as independent variables and crop yield as a dependent variable. It
subsequently compares the multiple linear regression (MLR) and PCR results, and
discusses the significance of PCR for crop yield estimation. In this context,
the book also covers Principal Component Analysis (PCA), a statistical procedure
used to reduce a number of correlated variables into a smaller number of
uncorrelated variables called principal components (PC). This book will be
helpful to the students and researchers, starting their works on climate and
agriculture, mainly focussing on estimation models. The flow of chapters takes
the readers in a smooth path, in understanding climate and weather and impact
of climate change, and gradually proceeds towards downscaling techniques and
then finally towards development of principal component regression models and
applying the same for the crop yield estimation.
Gujarat, especially with regard to the development of Multiple Regression
Models and Principal Component Regression (PCR) models using climatological
parameters as independent variables and crop yield as a dependent variable. It
subsequently compares the multiple linear regression (MLR) and PCR results, and
discusses the significance of PCR for crop yield estimation. In this context,
the book also covers Principal Component Analysis (PCA), a statistical procedure
used to reduce a number of correlated variables into a smaller number of
uncorrelated variables called principal components (PC). This book will be
helpful to the students and researchers, starting their works on climate and
agriculture, mainly focussing on estimation models. The flow of chapters takes
the readers in a smooth path, in understanding climate and weather and impact
of climate change, and gradually proceeds towards downscaling techniques and
then finally towards development of principal component regression models and
applying the same for the crop yield estimation.
Autoren-Porträt von T. M. V. Suryanarayana, P. B. Mistry
Dr. T. M. V. Suryanarayana is serving asAssociate 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.
Bibliographische Angaben
- Autoren: T. M. V. Suryanarayana , P. B. Mistry
- 2016, 1st ed. 2016, 67 Seiten, Englisch
- Verlag: Springer-Verlag GmbH
- ISBN-10: 9811006636
- ISBN-13: 9789811006630
- Erscheinungsdatum: 21.03.2016
Abhängig von Bildschirmgröße und eingestellter Schriftgröße kann die Seitenzahl auf Ihrem Lesegerät variieren.
eBook Informationen
- Dateiformat: PDF
- Größe: 2.26 MB
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Sprache:
Englisch
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