Application of finite sampling points in probability based multi: Objective optimization by means of the uniform experimental design
Introduction/purpose: An approximation for assessing a definite integral is continuously an attractive topic owing to its practical needs in scientific and engineering areas. An efficient approach for preliminarily calculating a definite integral with a small number of sampling points was newly...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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University of Defence in Belgrade
2022-07-01
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| Series: | Vojnotehnički Glasnik |
| Subjects: | |
| Online Access: | https://scindeks.ceon.rs/article.aspx?artid=0042-84692203636Z |
| _version_ | 1811238107903688704 |
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| author | Maosheng Zheng Haipeng Teng Yi Wang Jie Yu |
| author_facet | Maosheng Zheng Haipeng Teng Yi Wang Jie Yu |
| author_sort | Maosheng Zheng |
| collection | DOAJ |
| description | Introduction/purpose: An approximation for assessing a definite integral is
continuously an attractive topic owing to its practical needs in scientific
and engineering areas. An efficient approach for preliminarily calculating a
definite integral with a small number of sampling points was newly
developed to get an approximate value for a numerical integral with a
complicated integrand. In the present paper, an efficient approach with a
small number of sampling points is combined to the novel probability–
based multi–objective optimization (PMOO) by means of uniform
experimental design so as to simplify the complicated definite integral in
the PMOO preliminarily.
Methods: The distribution of sampling points within its single peak domain
is deterministic and uniform, which follows the rules of the uniform design
method and good lattice points; the total preferable probability is the
unique and deterministic index in the PMOO.
Results: The applications of the efficient approach with finite sampling
points in solving typical problems of PMOO indicate its rationality and
convenience in the operation.
Conclusion: The efficient approach with finite sampling points for
assessing a definite integral is successfully combined with PMOO by
means of the uniform design method and good lattice points. |
| first_indexed | 2024-04-12T12:36:01Z |
| format | Article |
| id | doaj.art-2a15db9da05b4a46874d73279416f95e |
| institution | Directory Open Access Journal |
| issn | 0042-8469 2217-4753 |
| language | English |
| last_indexed | 2024-04-12T12:36:01Z |
| publishDate | 2022-07-01 |
| publisher | University of Defence in Belgrade |
| record_format | Article |
| series | Vojnotehnički Glasnik |
| spelling | doaj.art-2a15db9da05b4a46874d73279416f95e2022-12-22T03:32:53ZengUniversity of Defence in BelgradeVojnotehnički Glasnik0042-84692217-47532022-07-0170363664910.5937/vojtehg70-37087Application of finite sampling points in probability based multi: Objective optimization by means of the uniform experimental designMaosheng Zheng0https://orcid.org/0000-0003-3361-4060Haipeng Teng1https://orcid.org/0000-0003-2987-7415Yi Wang2https://orcid.org/0000-0001-6711-0026Jie Yu3https://orcid.org/0000-0001-6606-5462Northwest University, School of Chemical Engineering, Xi’an, People's Republic of ChinaNorthwest University, School of Chemical Engineering, Xi’an, People's Republic of China Northwest University, School of Chemical Engineering, Xi’an, People's Republic of ChinaNorthwest University, School of Life Science, Xi’an, People's Republic of ChinaIntroduction/purpose: An approximation for assessing a definite integral is continuously an attractive topic owing to its practical needs in scientific and engineering areas. An efficient approach for preliminarily calculating a definite integral with a small number of sampling points was newly developed to get an approximate value for a numerical integral with a complicated integrand. In the present paper, an efficient approach with a small number of sampling points is combined to the novel probability– based multi–objective optimization (PMOO) by means of uniform experimental design so as to simplify the complicated definite integral in the PMOO preliminarily. Methods: The distribution of sampling points within its single peak domain is deterministic and uniform, which follows the rules of the uniform design method and good lattice points; the total preferable probability is the unique and deterministic index in the PMOO. Results: The applications of the efficient approach with finite sampling points in solving typical problems of PMOO indicate its rationality and convenience in the operation. Conclusion: The efficient approach with finite sampling points for assessing a definite integral is successfully combined with PMOO by means of the uniform design method and good lattice points.https://scindeks.ceon.rs/article.aspx?artid=0042-84692203636Zpreferable probabilitymulti–objective optimizationfinite sampling pointssimplifying evaluationuniform design method |
| spellingShingle | Maosheng Zheng Haipeng Teng Yi Wang Jie Yu Application of finite sampling points in probability based multi: Objective optimization by means of the uniform experimental design Vojnotehnički Glasnik preferable probability multi–objective optimization finite sampling points simplifying evaluation uniform design method |
| title | Application of finite sampling points in probability based multi: Objective optimization by means of the uniform experimental design |
| title_full | Application of finite sampling points in probability based multi: Objective optimization by means of the uniform experimental design |
| title_fullStr | Application of finite sampling points in probability based multi: Objective optimization by means of the uniform experimental design |
| title_full_unstemmed | Application of finite sampling points in probability based multi: Objective optimization by means of the uniform experimental design |
| title_short | Application of finite sampling points in probability based multi: Objective optimization by means of the uniform experimental design |
| title_sort | application of finite sampling points in probability based multi objective optimization by means of the uniform experimental design |
| topic | preferable probability multi–objective optimization finite sampling points simplifying evaluation uniform design method |
| url | https://scindeks.ceon.rs/article.aspx?artid=0042-84692203636Z |
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