Corn Nitrogen Nutrition Index Prediction Improved by Integrating Genetic, Environmental, and Management Factors with Active Canopy Sensing Using Machine Learning.
Dan LiYuxin MiaoCurtis J. RansomGregory Mac BeanNewell R. KitchenFabián G. FernándezJohn E. SawyerJames J. CamberatoPaul R. CarterRichard B. FergusonDavid W. FranzenCarrie A. M. LaboskiEmerson D. NafzigerJohn F. ShanahanPublished in: Remote. Sens. (2022)
Keyphrases
- machine learning
- management system
- environmental protection
- prediction accuracy
- environmental factors
- drinking water
- machine learning methods
- machine learning algorithms
- prediction model
- information management
- information extraction
- text classification
- natural resources
- prediction algorithm
- factors affecting
- real time
- genetic algorithm
- decision making
- pattern recognition
- sensor networks
- learning algorithm
- emergency management
- predictive modeling
- data processing
- factors that influence
- active learning
- human genome
- information systems
- index structure
- decision support
- knowledge acquisition
- database
- data analysis
- computer science
- reinforcement learning
- feature selection
- prediction error
- computer vision
- computational intelligence
- natural language processing
- artificial intelligence
- environmental information
- supervised learning
- knowledge representation