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Title: SENSITIVITY OF SPATIAL ANALYSIS NEURAL NETWORK TRAINING AND INTERPOLATION TO STRUCTURAL PARAMETERS

Author
item MARTINEZ, A - COLORADO STATE UNIVERSITY
item SALAS, J - COLORADO STATE UNIVERSITY
item Green, Timothy

Submitted to: Mathematical Geology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/9/2004
Publication Date: 8/1/2004
Citation: Martinez, A., Salas, J.D., Green, T.R. 2004. Sensitivity of spatial analysis neural network training and interpolation to structural parameters. Mathematical Geology. August 2004. Vol. 36, No. 6, pp. 721-742.

Interpretive Summary: This chapter emphasizes the design and implementation of the Object Modeling System OMS, an object-oriented framework for model development, testing, application and deployment. OMS facilitates the development of customized models from a library of science, data access, and utility module components, representing model building blocks. An overview about underlying design of components is given. OMS system parts are introduced and the application of the PRMS model in OMS is presented.

Technical Abstract: This chapter emphasizes the design and implementation of the Object Modeling System OMS, an object-oriented framework for model development, testing, application and deployment. OMS facilitates the development of customized models from a library of science, data access, and utility module components, representing model building blocks. An overview about underlying design of components is given. OMS system parts are introduced and the application of the PRMS model in OMS is presented.