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James D Keeler, John P Havener, Devendra Godbole, Ralph B Ferguson: Virtual continuous emission monitoring system with sensor validation. Pavilion Technologies, Gregory M Howison, January 31, 1995: US05386373 (208 worldwide citation)

A continuous emission monitoring system for a manufacturing plant (10) includes a control system (16) which has associated therewith a virtual sensor network (18). The network (18) is a predictive network that receives as inputs both control values to the plant (10) and also sensor values. The netwo ...


2
James David Keeler, John Paul Havener, Devendra Godbole, Ralph Bruce Ferguson II: Virtual emissions monitor for automobile and associated control system. Pavilion Technologies, Gregory M Howison, October 28, 1997: US05682317 (168 worldwide citation)

An internal combustion engine (360) is provided with a plurality of sensors to monitor the operation thereof with respect to various temperature measurements, pressure measurements, etc. A predictive model processor (322) is provided that utilizes model parameters stored in the memory (324) to predi ...


3
James D Keeler, John P Havener, Devendra Godbole, Ralph B Ferguson II: Virtual emissions monitor for automobile. Pavilion Technologies, Gregory M Howison, July 23, 1996: US05539638 (154 worldwide citation)

An internal combustion engine [(360)] is provided with a plurality of sensors to monitor the operation thereof with respect to various temperature measurements, pressure measurements, etc. A predictive model processor [(322)] is provided that utilizes model parameters stored in the memory [(324)] to ...


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James D Keeler, John P Havener, Devendra Godbole, Ralph B Ferguson: Virtual continuous emission monitoring system. Pavilion Technologies, Gregory M Howison, August 20, 1996: US05548528 (144 worldwide citation)

A continuous emission monitoring system for a manufacturing plant (10) includes a control system (16) which has associated therewith a virtual sensor network (18). The network (18) is a predictive network that receives as inputs both control values to the plant (10) and also sensor values. The netwo ...


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Stephen Piche, James David Keeler, Eric Hartman, William D Johnson, Mark Gerules, Kadir Liano: Method for steady-state identification based upon identified dynamics. Pavilion Technologies, Gregory M Howison, April 4, 2000: US06047221 (131 worldwide citation)

A method for modeling a steady-state network in the absence of steady-state historical data. A steady-state neural network can be tied by impressing the dynamics of the system onto the input data during the training operation by first determining the dynamics in a local region of the input space, th ...


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James David Keeler, Eric Jon Hartman, Ralph Bruce Ferguson: Method for operating a neural network with missing and/or incomplete data. Pavilion Technologies, Gregory M Howison, November 24, 1998: US05842189 (130 worldwide citation)

A neural network system is provided that models the system in a system model (12) with the output thereof providing a predicted output. This predicted output is modified or controlled by an output control (14). Input data is processed in a data preprocess step (10) to reconcile the data for input to ...


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James David Keeler, Eric Jon Hartman: Method and apparatus for analyzing a neural network within desired operating parameter constraints. Pavilion Technologies, Gregory M Howison, July 14, 1998: US05781432 (118 worldwide citation)

A distributed control system (14) receives on the input thereof the control inputs and then outputs control signals to a plant (10) for the operation thereof. The measured variables of the plant and the control inputs are input to a predictive model (34) that operates in conjunction with an inverse ...


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James D Keeler, Eric J Hartman, Kadir Liano, Ralph B Ferguson: Residual activation neural network. Pavilion Technologies, Ross Howison Clapp & Korn, October 4, 1994: US05353207 (114 worldwide citation)

A plant (72) is operable to receive control inputs c(t) and provide an output y(t). The plant (72) has associated therewith state variables s(t) that are not variable. A control network (74) is provided that accurately models the plant (72). The output of the control network (74) provides a predicte ...


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James D Keeler, Eric J Hartman, Steven A O Hara, Jill L Kempf, Devendra B Godbole: Method and apparatus for preprocessing input data to a neural network. Pavilion Technologies, Gregory M Howison, March 17, 1998: US05729661 (103 worldwide citation)

A preprocessing system for preprocessing input data to a neural network includes a training system for training a model (20) on data from a data file (10). The data is first preprocessed in a preprocessor (12) to fill in bad or missing data and merge all the time values on a common time scale. The p ...