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RECORD NUMBER: 6 OF 15

Main Title Optimal Weighting Function in Water Quality Modeling.
Author Lee, E. Stanley ; Misra., P. K. ;
CORP Author University of Southern California, Los Angeles. Dept. of Electrical Engineering.;National Science Foundation, Washington, D.C.;National Institutes of Health, Bethesda, Md.;Office of Water Resources Research, Washington, D.C.;Atomic Energy Commission, Washington, D.C.
Year Published 1973
Report Number USC-113P-56 ;RB73-23; DI-14-31-001-3678 ;AT(04-3)-113;
Stock Number PB-234 419
Additional Subjects Water quality ; Mathematical models ; Imbeddings(Mathematics) ; Differential equations ; Matrices(Mathematics) ; Estimates. Stream pollution ; NTISNSF ; NTISNIH
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NTIS  PB-234 419 Some EPA libraries have a fiche copy filed under the call number shown. 07/26/2022
Collation 36p
Abstract
In an earlier paper, the invariant imbedding concept was applied to the dynamic modeling of stream quality. In this approach, a set of weighting functions is introduced. The initial conditions for these weighting functions must be estimated. It has been found that these initial conditions influence the convergence rate tremendously. In many water quantity control situations, the number of experimental data points are limited. In order to obtain the best estimates with limited experimental data, the best convergence rate should be used. In this work, the least squares criterion combined with various optimization techniques is used to obtain the optimal initial conditions for the weighting functions. It is shown that the proposed schemes greatly improve the convergence rate.