Inversion Study of Nitrogen Content of Hyperspectral Apple Canopy Leaves Using Optimized Least Squares Support Vector Machine Approach
Abstract
:1. Introduction
2. Materials and Methods
2.1. Overview of the Study Area
2.2. Data Acquisition
2.2.1. Apple Canopy Leaf Hyperspectral Data Acquisition
2.2.2. Determination of Nitrogen Concentration in Apple Canopy Leaves
2.2.3. Spectral Data Preprocessing
2.3. Selection of Spectral Characteristics of Apple Leaves
2.4. Algorithm Fundamentals
2.4.1. Long- and Short-Term Memory Networks
2.4.2. Support Vector Regression
2.4.3. Least Squares Support Vector Machine Algorithm
2.4.4. Frost and Ice Optimization Algorithm (RIME)
2.5. Evaluation Metrics
3. Results
3.1. Selection of Features
3.1.1. Selection of Features by Continuous Projection Method
3.1.2. Competitive Adaptive Re-Weighting Method–Partial Least Squares
3.2. Inverse Modeling and Analysis of the Apple Leaf Nitrogen Content
3.2.1. Inverse Modeling Based on the Long Short-Term Memory Network, Support Vector Regression, and the RIME Optimization Algorithm Based on Least Squares Support Vector Machine Regression
3.2.2. Inverse Modeling Based on Long- and Short-Term Memory Networks
3.2.3. Inverse Modeling Based on Support Vector Regression
3.2.4. Inverse Modeling Based on the RIME Optimization Algorithm Based on Least Squares Support Vector Machine Regression
4. Discussion
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Extraction Method Characteristics | Inversion Model | R-Squared | RMSE | ||
---|---|---|---|---|---|
Training Set | Test Set | Training Set | Test Set | ||
SPA | LSTM | 0.6506 | 0.3307 | 0.1441 | 0.2097 |
CARS-PLS | LSTM | 0.7862 | 0.6155 | 0.0033 | 0.0041 |
SPA | SVR | 0.9238 | 0.4966 | 0.0672 | 0.1979 |
CARS-PLS | SVR | 0.9306 | 0.7468 | 0.0006 | 0.0014 |
SPA | RIME-LS-SVM | 0.9955 | 0.9404 | 0.0179 | 0.0637 |
CARS-PLS | RIME-LS-SVM | 0.998 | 0.964 | 0.0126 | 0.052 |
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Hou, K.; Bai, T.; Li, X.; Shi, Z.; Li, S. Inversion Study of Nitrogen Content of Hyperspectral Apple Canopy Leaves Using Optimized Least Squares Support Vector Machine Approach. Forests 2024, 15, 268. https://doi.org/10.3390/f15020268
Hou K, Bai T, Li X, Shi Z, Li S. Inversion Study of Nitrogen Content of Hyperspectral Apple Canopy Leaves Using Optimized Least Squares Support Vector Machine Approach. Forests. 2024; 15(2):268. https://doi.org/10.3390/f15020268
Chicago/Turabian StyleHou, Kaiyao, Tiecheng Bai, Xu Li, Ziyan Shi, and Senwei Li. 2024. "Inversion Study of Nitrogen Content of Hyperspectral Apple Canopy Leaves Using Optimized Least Squares Support Vector Machine Approach" Forests 15, no. 2: 268. https://doi.org/10.3390/f15020268
APA StyleHou, K., Bai, T., Li, X., Shi, Z., & Li, S. (2024). Inversion Study of Nitrogen Content of Hyperspectral Apple Canopy Leaves Using Optimized Least Squares Support Vector Machine Approach. Forests, 15(2), 268. https://doi.org/10.3390/f15020268