Found 7 datasets matching "Relevance vector machine".
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This paper explores how the remaining useful life (RUL) can be assessed for complex systems whose internal state variables are either inaccessible to sensors or hard to measure under operational...
Search relevance: 76.78 | Views last month: 0 -
Uncertainty management has always been the key hurdle faced by diagnostics and prognostics algorithms. A Bayesian treatment of this problem provides an elegant and theoretically sound approach to...
Search relevance: 73.82 | Views last month: 0 -
The estimation of remaining useful life (RUL) of a faulty component is at the center of system prognostics and health management. It gives operators a potent tool in decision making by quantifying...
Search relevance: 68.73 | Views last month: 1 -
The data set is composed of inputs and outputs of the DST demonstration and application to risk-based TMDLs and water quality risk assessment in Midwest river basins (Upper Mississippi River, Ohio...
Search relevance: 67.38 | Views last month: 0 -
The application of the Bayesian theory of managing uncertainty and complexity to regression and classification in the form of Relevance Vector Machine (RVM), and to state estimation via Particle...
Search relevance: 61.41 | Views last month: 2 -
In situations where the cost/benefit analysis of using physics-based damage propagation algorithms is not favorable and when sufficient test data are available that map out the damage space, one...
Search relevance: 60.52 | Views last month: 0 -
Prognostics has taken center stage in Condition Based Maintenance (CBM) where it is desired to estimate Remaining Useful Life (RUL) of a system so that remedial measures may be taken in advance to...
Search relevance: 54.13 | Views last month: 0
