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Online Parameter Selection for Gas Distribution Mapping
| Content Provider | CiteSeerX |
|---|---|
| Author | Lilienthala, Achim J. Schaffernichta, Erik Trincavellia, Marco Hern, Victor Bennettsa, Ez Pomaredab, Victor |
| Abstract | Abstract- The ability to produce truthful maps of the distribution of one or more gases is beneficial for applicat ions ranging from environmental monitoring to mines and industrial plants surveillance. Realistic environments are often too complicated for applying analytical gas plume models or performing reliab le CFD simulations, making data-driven statistical gas distribution models the most attractive alternative. However, statistical models for gas distribution modelling, often rely on a set of meta-parameters that need to be learned from the data through Cross Validation (CV) techniques. CV techniques are computationally expensive and therefore need to be computed offline. As a faster alternative, we propose a parameter selection method based on Virtual Leave-One-Out Cross Validation (VLOOCV) that enables online learning of meta-parameters. In particular, we consider the Kernel DM+V, one of the most well studied algorithms for statistical gas distribution mapping, which relies on a meta-parameter, the kernel bandwidth. We validate the proposed VLOOCV method on a set of indoor and outdoor experiments where a mobile robot with a Photo Ionization Detector (PID) was collecting gas measurements. The approximation provided by the proposed VLOOCV method achieves very similar results to plain Cross Validation at a fraction of the computational cost. This is an important step in the development of on-line statistical gas distribution modelling algorithms. |
| File Format | |
| Access Restriction | Open |
| Subject Keyword | Cv Technique Parameter Selection Method Data-driven Statistical Gas Distribution Model Gas Measurement Industrial Plant Surveillance Photo Ionization Detector Applicat Ion Gas Distribution Mapping Reliab Le Cfd Simulation Gas Distribution Modelling Kernel Bandwidth Realistic Environment On-line Statistical Gas Distribution Kernel Dm Analytical Gas Plume Model Vloocv Method Virtual Leave-one-out Cross Validation Online Parameter Selection Studied Algorithm Cross Validation Outdoor Experiment Statistical Gas Distribution Mapping Truthful Map |
| Content Type | Text |
| Resource Type | Article |
