OPTIMAL SELECTION FOR THE WEIGHTED COEFFICIENTS OF THE CONSTRAINED VARIATIONAL PROBLEMS
The aim is to put forward the optimal selecting of weights in variational problem in which the linear advection equation is used as constraint. The selection of the functional weight coefficients (FWC) is one of the key problems for the relevant research. It was arbitrary and subjective to some exte...
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| Published in | Applied mathematics and mechanics Vol. 24; no. 8; pp. 936 - 944 |
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| Main Author | |
| Format | Journal Article |
| Language | English |
| Published |
Key Laboratory of Mesoscale Severe Weather, Ministry of Education, Narjing University, Nanjing 210093, P.R.China%School of Science, Nanjing University of Technology, Nanjing 210009, P.R. China%National Severe Storms Laboratory, NOAA, 1313 Halley Circle Norman, OK 73069, USA
01.08.2003
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0253-4827 1573-2754 |
| DOI | 10.1007/bf02446499 |
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| Abstract | The aim is to put forward the optimal selecting of weights in variational problem in which the linear advection equation is used as constraint. The selection of the functional weight coefficients (FWC) is one of the key problems for the relevant research. It was arbitrary and subjective to some extent presently. To overcome this difficulty, the reasonable assumptions were given for the observation field and analyzed field, variational problems with “weak constraints” and “strong constraints” were considered separately. By solving Euler' s equation with the matrix theory and the finite difference method of partial differential equation, the objective weight coefficients were obtained in the minimum variance of the difference between the analyzed field and ideal field. Deduction results show that theoretically the optimal selection indeed exists in the weighting factors of the cost function in the means of the minimal variance between the analysis and ideal field in terms of the matrix theory and partial differential (corresponding difference ) equation, if the reasonable assumption from the actual problem is valid and the differnece equation is stable. It may realize the coordination among the weight factors, numerical models and the observational data. With its theoretical basis as well as its prospects of applications, this objective selecting method is probably a way towards the finding of the optimal weighting factors in the variational problem. |
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| AbstractList | The aim is to put forward the optimal selecting of weights in variational problem in which the linear advection equation is used as constraint. The selection of the functional weight coefficients (FWC) is one of the key problems for the relevant research. It was arbitrary and subjective to some extent presently. To overcome this difficulty, the reasonable assumptions were given for the observation field and analyzed field, variational problems with “weak constraints” and “strong constraints” were considered separately. By solving Euler' s equation with the matrix theory and the finite difference method of partial differential equation, the objective weight coefficients were obtained in the minimum variance of the difference between the analyzed field and ideal field. Deduction results show that theoretically the optimal selection indeed exists in the weighting factors of the cost function in the means of the minimal variance between the analysis and ideal field in terms of the matrix theory and partial differential (corresponding difference ) equation, if the reasonable assumption from the actual problem is valid and the differnece equation is stable. It may realize the coordination among the weight factors, numerical models and the observational data. With its theoretical basis as well as its prospects of applications, this objective selecting method is probably a way towards the finding of the optimal weighting factors in the variational problem. O177.92; The aim is to put forward the optimal selecting of weights in variational problem in which the linear advection equation is used as constraint. The selection of the functional weight coefficients (FWC) is one of the key problems for the relevant research. It was arbitrary and subjective to some extent presently. To overcome this difficulty, the reasonable assumptions were given for the observation field and analyz ed field, variational problems with "weak constraints" and "strong constraints" were considered separately. By solving Euler' s equation with the matrix theory and the finite difference method of partial differential equation, the objective weight coefficients were obtained in the minimum variance of the difference between the analyzed field and ideal field. Deduction results show that theoretically the optimal selection indeed exists in the weighting factors of the cost function in the means of the minimal variance between the analysis and ideal field in terms of the matrix theory and partial differential ( corresponding difference ) equation, if the reasonable assumption from the actual problem is valid and the differnece equation is stable.It may realize the coordination among the weight factors, numerical models and the observational data. With its theoretical basis as well as its prospects of applications, this objective selecting method is probably a way towards the finding of the optimal weighting factors in the variational problem. |
| Author | 魏鸣 刘国庆 王成刚 葛文忠 许秦 |
| AuthorAffiliation | KeyLaboratoryofMesoscaleSevereWeather,MinislryofEducation,NanjingUniversity,Nanjing210093,P.R.China SchoolofScience,NanjingUniversityofTechnology,Nanjing210009,P.R.China NationalSevereStormsLaboratory,NOAA,1313HalleyCircleNorman,OK73069,USA |
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| Cites_doi | 10.1175/1520-0426(1995)012<1111:AMROLA>2.0.CO;2 10.1175/1520-0426(1992)009<0588:ASAMOW>2.0.CO;2 10.1007/s00376-998-0032-6 10.1175/1520-0426(1994)011<0289:SAMFSD>2.0.CO;2 10.1175/1520-0493(1970)098<0875:SBFINV>2.3.CO;2 10.1175/1520-0469(1991)048<0876:ROTDWA>2.0.CO;2 |
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| Publisher | Key Laboratory of Mesoscale Severe Weather, Ministry of Education, Narjing University, Nanjing 210093, P.R.China%School of Science, Nanjing University of Technology, Nanjing 210009, P.R. China%National Severe Storms Laboratory, NOAA, 1313 Halley Circle Norman, OK 73069, USA |
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| References | Y K Sasaki (BF02446499_CR8) 1970; 98 Xu Qin (BF02446499_CR5) 1994; 11 Liu Guo-qing (BF02446499_CR2) 1995; 17 J Sun (BF02446499_CR4) 1991; 48 Xu Qin (BF02446499_CR7) 1995; 123 Qiu Chong-jian (BF02446499_CR3) 1992; 9 Chou Ji-fan (BF02446499_CR1) 1995 Xu Qin (BF02446499_CR6) 1995; 12 Wei Ming (BF02446499_CR9) 1998; 15 |
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| Snippet | The aim is to put forward the optimal selecting of weights in variational problem in which the linear advection equation is used as constraint. The selection... O177.92; The aim is to put forward the optimal selecting of weights in variational problem in which the linear advection equation is used as constraint. The... |
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| SubjectTerms | 加权系数 变分问题 最优化 最小方差 |
| Title | OPTIMAL SELECTION FOR THE WEIGHTED COEFFICIENTS OF THE CONSTRAINED VARIATIONAL PROBLEMS |
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