| 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
|
| Holdings |
| Library |
Call Number |
Additional Info |
Location |
Last
Modified |
Checkout
Status |
| 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. |
