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Found 4 papers, 2 papers with code
Physics-informed machine learning for Structural Health Monitoring
The chapter will demonstrate how grey-box models, that combine simple physics-based models with data-driven ones, can improve predictive capability in an SHM setting.
BIG-bench Machine Learning
Physics-informed machine learning
+1
GACAN: Graph Attention-Convolution-Attention Networks for Traffic Forecasting Based on Multi-granularity Time Series
The main novelty of the model is the integration of time series of four different time granularities: the original time series, together with hourly, daily, and weekly time series.
Canonical-Correlation-Based Fast Feature Selection
The supporting theorems developed for the feature selection method are fundamental to the understanding of the canonical correlation analysis.
Orthogonal Least Squares Based Fast Feature Selection for Linear Classification
The proposed method is comprehensively compared with the mutual information based feature selection methods and the embedded methods using both synthetic and real world datasets.
