Predicting the state of charge and health of batteries using data-driven machine learning.
Man-Fai NgJin ZhaoQingyu YanGareth John ConduitZhi Wei SehPublished in: Nat. Mach. Intell. (2020)
Keyphrases
- data driven
- machine learning
- data mining
- learning algorithm
- information extraction
- active learning
- pattern recognition
- text classification
- machine learning methods
- computer science
- learning systems
- machine learning algorithms
- health care
- feature selection
- computer vision
- artificial intelligence
- learning tasks
- knowledge representation
- energy consumption
- unsupervised learning
- inductive learning
- knowledge acquisition
- computational intelligence
- text mining
- natural language processing
- support vector machine
- computational biology
- social networks
- medical care
- explanation based learning
- machine learning and data mining
- chronic disease
- databases
- statistical methods
- model selection
- data analysis
- training data
- case study
- decision trees
- neural network