Data processing: artificial intelligence – Neural network
Reexamination Certificate
2007-03-13
2007-03-13
Hirl, Joseph P. (Department: 2129)
Data processing: artificial intelligence
Neural network
C706S021000, C706S026000
Reexamination Certificate
active
10637087
ABSTRACT:
A method and system for data modeling that incorporates the advantages of both traditional response surface methodology (RSM) and neural networks is disclosed. The invention partitions the parameters into a first set of s simple parameters, where observable data are expressible as low order polynomials, and c complex parameters that reflect more complicated variation of the observed data. Variation of the data with the simple parameters is modeled using polynomials; and variation of the data with the complex parameters at each vertex is analyzed using a neural network. Variations with the simple parameters and with the complex parameters are expressed using a first sequence of shape functions and a second sequence of neural network functions. The first and second sequences are multiplicatively combined to form a composite response surface, dependent upon the parameter values, that can be used to identify an accurate model.
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Madavan Nateri K.
Rai Man Mohan
Hirl Joseph P.
Padilla Robert M.
Schipper John F.
The United States of America as represented by the Administrator
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