Pavilion Technologies, Inc.
58Patents
1Active
58Granted
38Portfolio score
Filing activity: Jun 10, 1992 → Apr 3, 2006 · 1 expiring within 5 years
Most-cited patents
| Patent | Title | Area | Cited by | Status |
|---|---|---|---|---|
| US5386373A | Virtual continuous emission monitoring system with sensor validation | Mechanical Engineering; Lighting; Heating | 373 | Expired |
| US6278899A | Method for on-line optimization of a plant | Physics | 220 | Expired |
| US5682317A | Virtual emissions monitor for automobile and associated control system | Physics | 216 | Expired |
| US5842189A | Method for operating a neural network with missing and/or incomplete data | Physics | 199 | Expired |
| US5539638A | Virtual emissions monitor for automobile | Physics | 196 | Expired |
| US5548528A | Virtual continuous emission monitoring system | Mechanical Engineering; Lighting; Heating | 181 | Expired |
| US6047221A | Method for steady-state identification based upon identified dynamics | Physics | 158 | Expired |
| US5781432A | Method and apparatus for analyzing a neural network within desired operating parameter constraints | Mechanical Engineering; Lighting; Heating | 137 | Expired |
| US5353207A | Residual activation neural network | Emerging Cross-Sectional Technologies | 132 | Expired |
| US5729661A | Method and apparatus for preprocessing input data to a neural network | Physics | 124 | Expired |
| US6725208B1 | Bayesian neural networks for optimization and control | Emerging Cross-Sectional Technologies | 116 | Expired |
| US6934931B2 | System and method for enterprise modeling, optimization and control | Physics | 115 | Expired |
| US5825646A | Method and apparatus for determining the sensitivity of inputs to a neural network on output parameters | Physics | 113 | Expired |
| US5559690A | Residual activation neural network | Emerging Cross-Sectional Technologies | 100 | Expired |
| US5933345A | Method and apparatus for dynamic and steady state modeling over a desired path between two end points | Physics | 100 | Expired |
| US6243696A | Automated method for building a model | Emerging Cross-Sectional Technologies | 96 | Expired |
| US6381504B1 | Method for optimizing a plant with multiple inputs | Physics | 88 | Expired |
| US5859773A | Residual activation neural network | Emerging Cross-Sectional Technologies | 84 | Expired |
| US7050866B2 | Dynamic controller for controlling a system | Physics | 72 | Expired |
| US6487459B1 | Method and apparatus for modeling dynamic and steady-state processes for prediction, control and optimization | Physics | 69 | Expired |
| US5479573A | Predictive network with learned preprocessing parameters | Physics | 67 | Expired |
| US7039475B2 | System and method of adaptive control of processes with varying dynamics | Physics | 64 | Expired |
| US6169980A | Method for operating a neural network with missing and/or incomplete data | Physics | 59 | Expired |
| US7058617B1 | Method and apparatus for training a system model with gain constraints | Physics | 58 | Expired |
| US6944616B2 | System and method for historical database training of support vector machines | Emerging Cross-Sectional Technologies | 55 | Expired |
Source: USPTO / EPO open patent data. Counts and citation impact are objective bibliographic measures.