Predicting the sugarcane yield in real-time by harvester engine parameters and machine learning approaches.
Leonardo Felipe MaldanerLucas de Paula CorrêdoTatiana Fernanda CanataJosé Paulo MolinPublished in: Comput. Electron. Agric. (2021)
Keyphrases
- machine learning approaches
- real time
- machine learning algorithms
- machine learning
- machine learning methods
- machine learning models
- decision trees
- control system
- sensitivity analysis
- pattern analysis
- parameter estimation
- parameter values
- data sources
- maximum likelihood
- expectation maximization
- image segmentation
- input parameters
- genetic algorithm