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The Resource Principal Component Regression for Crop Yield Estimation

Principal Component Regression for Crop Yield Estimation

Label
Principal Component Regression for Crop Yield Estimation
Title
Principal Component Regression for Crop Yield Estimation
Creator
Contributor
Subject
Language
eng
Member of
Cataloging source
MiAaPQ
Literary form
non fiction
Nature of contents
dictionaries
Series statement
SpringerBriefs in Applied Sciences and Technology Ser
Principal Component Regression for Crop Yield Estimation
Label
Principal Component Regression for Crop Yield Estimation
Link
http://libproxy.rpi.edu/login?url=https://ebookcentral.proquest.com/lib/rpi/detail.action?docID=4454939
Publication
Copyright
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Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
  • Preface -- Acknowledgment -- Contents -- About the Authors -- List of Figures -- List of Tables -- 1 Introduction -- Abstract -- 1.1 Climate and Weather -- 1.2 Climate Change -- 1.3 Impact of Climate Change in Global Context -- 1.4 Impact of Climate Change on Agriculture -- 1.5 Climatological Parameters Affecting Crop Yeild -- 1.5.1 Maximum and Minimum Temperature -- 1.5.2 Relative Humidity -- 1.5.3 Wind Speed -- 1.5.4 Sunshine Hours -- 1.6 Downscaling -- 1.6.1 Uncertainty -- 1.7 Downscaling Techniques and Their Application -- 1.7.1 Dynamical Downscaling -- 1.7.2 Statistical Downscaling -- 1.7.3 Statistical-Dynamical Downscaling -- 1.8 Multiple Linear Regression -- 1.9 Principal Component Analysis (PCA) -- 1.10 Objectives -- 2 Principal Component Analysis in Transfer Function -- Abstract -- 2.1 Transfer Function/Regression Method -- 2.2 Types of Regressions -- 2.2.1 The Simple Linear Regression Model -- 2.2.2 The Multiple Linear Regression Model -- 2.2.3 Polynomial Regression Models -- 2.2.4 Nonlinear Regression -- 2.3 Principal Component Analysis (PCA) -- 2.3.1 Advantages and Disadvantages of PCA -- 2.3.2 Applications of Principal Components -- 2.4 Principal Component Regression (PCR) -- 2.4.1 Calculating Principal Components -- 2.4.2 Rules for Retaining Principal Components -- 2.4.3 Development of Principal Component Regression (PCR) -- 3 Review of Literature -- Abstract -- 3.1 Review of Works on Climate Change -- 3.2 Review of Works on Downscaling Techniques -- 3.3 Review of Works on Multiple Linear Regressions -- 3.4 Review of Works on Principal Component Analysis and Principal Component Regression -- 4 Study Area and Data Collection -- Abstract -- 4.1 Agroclimatic Zones by the Planning Commission -- 4.2 Subagroclimatic Zones of Gujarat -- 4.2.1 Southern Hills -- 4.2.2 Southern Gujarat -- 4.2.3 Middle Gujarat -- 4.2.4 North Gujarat
  • 4.2.5 Northwest Arid -- 4.2.6 North Saurashtra -- 4.2.7 South Saurashtra -- 4.3 Study Area -- 4.4 Data Collection -- 5 Methodology -- Abstract -- 5.1 Multiple Linear Regression Model -- 5.2 Principal Component Regression Model -- 5.3 Performance Indices -- 5.3.1 Root Mean Squared Error (RMSE) -- 5.3.2 Correlation Coefficient (r) -- 5.3.3 Coefficient of Determination (R2) -- 5.3.4 Discrepancy Ratio (D.R.) -- 5.4 Analysis of MLR and PCR Models -- 6 Results and Analysis -- Abstract -- 6.1 MLR Model During Training and Validation -- 6.1.1 Multiple Linear Regression During Training -- 6.1.2 Multiple Linear Regression During Validation -- 6.2 PCR Model During Training and Validation -- 6.2.1 Principal Component Regression During Training -- 6.2.2 PCR During Validation -- 6.3 Comparison of MLR and PCR Models Using Performance Indices -- 6.4 Analysis of MLR and PCR Models Developed -- 7 Conclusions -- Abstract -- 7.1 Conclusions Based on the Study -- References -- Online Documents
http://library.link/vocab/cover_art
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Dimensions
unknown
http://library.link/vocab/discovery_link
{'f': 'http://opac.lib.rpi.edu/record=b4385027'}
Extent
1 online resource (77 pages)
Form of item
online
Isbn
9789811006630
Media category
computer
Media MARC source
rdamedia
Media type code
c
Sound
unknown sound
Specific material designation
remote

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