An interval model updating strategy using interval response surface models
Stochastic model updating provides an effective way of handling uncertainties existing in real-world structures. In general, probabilistic theories, fuzzy mathematics or interval analyses are involved in the solution of inverse problems. However in practice, probability distributions or membership f...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Fang, Sheng-En [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2015transfer abstract |
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| Schlagwörter: |
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| Umfang: |
19 |
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| Übergeordnetes Werk: |
Enthalten in: Species loss from land use of oil palm plantations in Thailand - Jaroenkietkajorn, Ukrit ELSEVIER, 2021, mssp, Amsterdam [u.a.] |
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| Übergeordnetes Werk: |
volume:60 ; year:2015 ; pages:909-927 ; extent:19 |
| Links: |
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| DOI / URN: |
10.1016/j.ymssp.2015.01.016 |
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ELV023792523 |
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| 520 | |a Stochastic model updating provides an effective way of handling uncertainties existing in real-world structures. In general, probabilistic theories, fuzzy mathematics or interval analyses are involved in the solution of inverse problems. However in practice, probability distributions or membership functions of structural parameters are often unavailable due to insufficient information of a structure. At this moment an interval model updating procedure shows its superiority in the aspect of problem simplification since only the upper and lower bounds of parameters and responses are sought. To this end, this study develops a new concept of interval response surface models for the purpose of efficiently implementing the interval model updating procedure. The frequent interval overestimation due to the use of interval arithmetic can be maximally avoided leading to accurate estimation of parameter intervals. Meanwhile, the establishment of an interval inverse problem is highly simplified, accompanied by a saving of computational costs. By this means a relatively simple and cost-efficient interval updating process can be achieved. Lastly, the feasibility and reliability of the developed method have been verified against a numerical mass–spring system and also against a set of experimentally tested steel plates. | ||
| 520 | |a Stochastic model updating provides an effective way of handling uncertainties existing in real-world structures. In general, probabilistic theories, fuzzy mathematics or interval analyses are involved in the solution of inverse problems. However in practice, probability distributions or membership functions of structural parameters are often unavailable due to insufficient information of a structure. At this moment an interval model updating procedure shows its superiority in the aspect of problem simplification since only the upper and lower bounds of parameters and responses are sought. To this end, this study develops a new concept of interval response surface models for the purpose of efficiently implementing the interval model updating procedure. The frequent interval overestimation due to the use of interval arithmetic can be maximally avoided leading to accurate estimation of parameter intervals. Meanwhile, the establishment of an interval inverse problem is highly simplified, accompanied by a saving of computational costs. By this means a relatively simple and cost-efficient interval updating process can be achieved. Lastly, the feasibility and reliability of the developed method have been verified against a numerical mass–spring system and also against a set of experimentally tested steel plates. | ||
| 650 | 7 | |a Interval response surface models |2 Elsevier | |
| 650 | 7 | |a Interval inverse problem |2 Elsevier | |
| 650 | 7 | |a Interval overestimation. |2 Elsevier | |
| 650 | 7 | |a Interval model updating |2 Elsevier | |
| 650 | 7 | |a Interval arithmetic |2 Elsevier | |
| 700 | 1 | |a Zhang, Qiu-Hu |4 oth | |
| 700 | 1 | |a Ren, Wei-Xin |4 oth | |
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10.1016/j.ymssp.2015.01.016 doi GBVA2015015000017.pica (DE-627)ELV023792523 (ELSEVIER)S0888-3270(15)00022-9 DE-627 ger DE-627 rakwb eng 004 004 DE-600 570 630 VZ BIODIV DE-30 fid Fang, Sheng-En verfasserin aut An interval model updating strategy using interval response surface models 2015transfer abstract 19 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Stochastic model updating provides an effective way of handling uncertainties existing in real-world structures. In general, probabilistic theories, fuzzy mathematics or interval analyses are involved in the solution of inverse problems. However in practice, probability distributions or membership functions of structural parameters are often unavailable due to insufficient information of a structure. At this moment an interval model updating procedure shows its superiority in the aspect of problem simplification since only the upper and lower bounds of parameters and responses are sought. To this end, this study develops a new concept of interval response surface models for the purpose of efficiently implementing the interval model updating procedure. The frequent interval overestimation due to the use of interval arithmetic can be maximally avoided leading to accurate estimation of parameter intervals. Meanwhile, the establishment of an interval inverse problem is highly simplified, accompanied by a saving of computational costs. By this means a relatively simple and cost-efficient interval updating process can be achieved. Lastly, the feasibility and reliability of the developed method have been verified against a numerical mass–spring system and also against a set of experimentally tested steel plates. Stochastic model updating provides an effective way of handling uncertainties existing in real-world structures. In general, probabilistic theories, fuzzy mathematics or interval analyses are involved in the solution of inverse problems. However in practice, probability distributions or membership functions of structural parameters are often unavailable due to insufficient information of a structure. At this moment an interval model updating procedure shows its superiority in the aspect of problem simplification since only the upper and lower bounds of parameters and responses are sought. To this end, this study develops a new concept of interval response surface models for the purpose of efficiently implementing the interval model updating procedure. The frequent interval overestimation due to the use of interval arithmetic can be maximally avoided leading to accurate estimation of parameter intervals. Meanwhile, the establishment of an interval inverse problem is highly simplified, accompanied by a saving of computational costs. By this means a relatively simple and cost-efficient interval updating process can be achieved. Lastly, the feasibility and reliability of the developed method have been verified against a numerical mass–spring system and also against a set of experimentally tested steel plates. Interval response surface models Elsevier Interval inverse problem Elsevier Interval overestimation. Elsevier Interval model updating Elsevier Interval arithmetic Elsevier Zhang, Qiu-Hu oth Ren, Wei-Xin oth Enthalten in Elsevier Jaroenkietkajorn, Ukrit ELSEVIER Species loss from land use of oil palm plantations in Thailand 2021 mssp Amsterdam [u.a.] (DE-627)ELV007151810 volume:60 year:2015 pages:909-927 extent:19 https://doi.org/10.1016/j.ymssp.2015.01.016 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA AR 60 2015 909-927 19 045F 004 |
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10.1016/j.ymssp.2015.01.016 doi GBVA2015015000017.pica (DE-627)ELV023792523 (ELSEVIER)S0888-3270(15)00022-9 DE-627 ger DE-627 rakwb eng 004 004 DE-600 570 630 VZ BIODIV DE-30 fid Fang, Sheng-En verfasserin aut An interval model updating strategy using interval response surface models 2015transfer abstract 19 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Stochastic model updating provides an effective way of handling uncertainties existing in real-world structures. In general, probabilistic theories, fuzzy mathematics or interval analyses are involved in the solution of inverse problems. However in practice, probability distributions or membership functions of structural parameters are often unavailable due to insufficient information of a structure. At this moment an interval model updating procedure shows its superiority in the aspect of problem simplification since only the upper and lower bounds of parameters and responses are sought. To this end, this study develops a new concept of interval response surface models for the purpose of efficiently implementing the interval model updating procedure. The frequent interval overestimation due to the use of interval arithmetic can be maximally avoided leading to accurate estimation of parameter intervals. Meanwhile, the establishment of an interval inverse problem is highly simplified, accompanied by a saving of computational costs. By this means a relatively simple and cost-efficient interval updating process can be achieved. Lastly, the feasibility and reliability of the developed method have been verified against a numerical mass–spring system and also against a set of experimentally tested steel plates. Stochastic model updating provides an effective way of handling uncertainties existing in real-world structures. In general, probabilistic theories, fuzzy mathematics or interval analyses are involved in the solution of inverse problems. However in practice, probability distributions or membership functions of structural parameters are often unavailable due to insufficient information of a structure. At this moment an interval model updating procedure shows its superiority in the aspect of problem simplification since only the upper and lower bounds of parameters and responses are sought. To this end, this study develops a new concept of interval response surface models for the purpose of efficiently implementing the interval model updating procedure. The frequent interval overestimation due to the use of interval arithmetic can be maximally avoided leading to accurate estimation of parameter intervals. Meanwhile, the establishment of an interval inverse problem is highly simplified, accompanied by a saving of computational costs. By this means a relatively simple and cost-efficient interval updating process can be achieved. Lastly, the feasibility and reliability of the developed method have been verified against a numerical mass–spring system and also against a set of experimentally tested steel plates. Interval response surface models Elsevier Interval inverse problem Elsevier Interval overestimation. Elsevier Interval model updating Elsevier Interval arithmetic Elsevier Zhang, Qiu-Hu oth Ren, Wei-Xin oth Enthalten in Elsevier Jaroenkietkajorn, Ukrit ELSEVIER Species loss from land use of oil palm plantations in Thailand 2021 mssp Amsterdam [u.a.] (DE-627)ELV007151810 volume:60 year:2015 pages:909-927 extent:19 https://doi.org/10.1016/j.ymssp.2015.01.016 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA AR 60 2015 909-927 19 045F 004 |
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10.1016/j.ymssp.2015.01.016 doi GBVA2015015000017.pica (DE-627)ELV023792523 (ELSEVIER)S0888-3270(15)00022-9 DE-627 ger DE-627 rakwb eng 004 004 DE-600 570 630 VZ BIODIV DE-30 fid Fang, Sheng-En verfasserin aut An interval model updating strategy using interval response surface models 2015transfer abstract 19 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Stochastic model updating provides an effective way of handling uncertainties existing in real-world structures. In general, probabilistic theories, fuzzy mathematics or interval analyses are involved in the solution of inverse problems. However in practice, probability distributions or membership functions of structural parameters are often unavailable due to insufficient information of a structure. At this moment an interval model updating procedure shows its superiority in the aspect of problem simplification since only the upper and lower bounds of parameters and responses are sought. To this end, this study develops a new concept of interval response surface models for the purpose of efficiently implementing the interval model updating procedure. The frequent interval overestimation due to the use of interval arithmetic can be maximally avoided leading to accurate estimation of parameter intervals. Meanwhile, the establishment of an interval inverse problem is highly simplified, accompanied by a saving of computational costs. By this means a relatively simple and cost-efficient interval updating process can be achieved. Lastly, the feasibility and reliability of the developed method have been verified against a numerical mass–spring system and also against a set of experimentally tested steel plates. Stochastic model updating provides an effective way of handling uncertainties existing in real-world structures. In general, probabilistic theories, fuzzy mathematics or interval analyses are involved in the solution of inverse problems. However in practice, probability distributions or membership functions of structural parameters are often unavailable due to insufficient information of a structure. At this moment an interval model updating procedure shows its superiority in the aspect of problem simplification since only the upper and lower bounds of parameters and responses are sought. To this end, this study develops a new concept of interval response surface models for the purpose of efficiently implementing the interval model updating procedure. The frequent interval overestimation due to the use of interval arithmetic can be maximally avoided leading to accurate estimation of parameter intervals. Meanwhile, the establishment of an interval inverse problem is highly simplified, accompanied by a saving of computational costs. By this means a relatively simple and cost-efficient interval updating process can be achieved. Lastly, the feasibility and reliability of the developed method have been verified against a numerical mass–spring system and also against a set of experimentally tested steel plates. Interval response surface models Elsevier Interval inverse problem Elsevier Interval overestimation. Elsevier Interval model updating Elsevier Interval arithmetic Elsevier Zhang, Qiu-Hu oth Ren, Wei-Xin oth Enthalten in Elsevier Jaroenkietkajorn, Ukrit ELSEVIER Species loss from land use of oil palm plantations in Thailand 2021 mssp Amsterdam [u.a.] (DE-627)ELV007151810 volume:60 year:2015 pages:909-927 extent:19 https://doi.org/10.1016/j.ymssp.2015.01.016 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA AR 60 2015 909-927 19 045F 004 |
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10.1016/j.ymssp.2015.01.016 doi GBVA2015015000017.pica (DE-627)ELV023792523 (ELSEVIER)S0888-3270(15)00022-9 DE-627 ger DE-627 rakwb eng 004 004 DE-600 570 630 VZ BIODIV DE-30 fid Fang, Sheng-En verfasserin aut An interval model updating strategy using interval response surface models 2015transfer abstract 19 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Stochastic model updating provides an effective way of handling uncertainties existing in real-world structures. In general, probabilistic theories, fuzzy mathematics or interval analyses are involved in the solution of inverse problems. However in practice, probability distributions or membership functions of structural parameters are often unavailable due to insufficient information of a structure. At this moment an interval model updating procedure shows its superiority in the aspect of problem simplification since only the upper and lower bounds of parameters and responses are sought. To this end, this study develops a new concept of interval response surface models for the purpose of efficiently implementing the interval model updating procedure. The frequent interval overestimation due to the use of interval arithmetic can be maximally avoided leading to accurate estimation of parameter intervals. Meanwhile, the establishment of an interval inverse problem is highly simplified, accompanied by a saving of computational costs. By this means a relatively simple and cost-efficient interval updating process can be achieved. Lastly, the feasibility and reliability of the developed method have been verified against a numerical mass–spring system and also against a set of experimentally tested steel plates. Stochastic model updating provides an effective way of handling uncertainties existing in real-world structures. In general, probabilistic theories, fuzzy mathematics or interval analyses are involved in the solution of inverse problems. However in practice, probability distributions or membership functions of structural parameters are often unavailable due to insufficient information of a structure. At this moment an interval model updating procedure shows its superiority in the aspect of problem simplification since only the upper and lower bounds of parameters and responses are sought. To this end, this study develops a new concept of interval response surface models for the purpose of efficiently implementing the interval model updating procedure. The frequent interval overestimation due to the use of interval arithmetic can be maximally avoided leading to accurate estimation of parameter intervals. Meanwhile, the establishment of an interval inverse problem is highly simplified, accompanied by a saving of computational costs. By this means a relatively simple and cost-efficient interval updating process can be achieved. Lastly, the feasibility and reliability of the developed method have been verified against a numerical mass–spring system and also against a set of experimentally tested steel plates. Interval response surface models Elsevier Interval inverse problem Elsevier Interval overestimation. Elsevier Interval model updating Elsevier Interval arithmetic Elsevier Zhang, Qiu-Hu oth Ren, Wei-Xin oth Enthalten in Elsevier Jaroenkietkajorn, Ukrit ELSEVIER Species loss from land use of oil palm plantations in Thailand 2021 mssp Amsterdam [u.a.] (DE-627)ELV007151810 volume:60 year:2015 pages:909-927 extent:19 https://doi.org/10.1016/j.ymssp.2015.01.016 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA AR 60 2015 909-927 19 045F 004 |
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10.1016/j.ymssp.2015.01.016 doi GBVA2015015000017.pica (DE-627)ELV023792523 (ELSEVIER)S0888-3270(15)00022-9 DE-627 ger DE-627 rakwb eng 004 004 DE-600 570 630 VZ BIODIV DE-30 fid Fang, Sheng-En verfasserin aut An interval model updating strategy using interval response surface models 2015transfer abstract 19 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Stochastic model updating provides an effective way of handling uncertainties existing in real-world structures. In general, probabilistic theories, fuzzy mathematics or interval analyses are involved in the solution of inverse problems. However in practice, probability distributions or membership functions of structural parameters are often unavailable due to insufficient information of a structure. At this moment an interval model updating procedure shows its superiority in the aspect of problem simplification since only the upper and lower bounds of parameters and responses are sought. To this end, this study develops a new concept of interval response surface models for the purpose of efficiently implementing the interval model updating procedure. The frequent interval overestimation due to the use of interval arithmetic can be maximally avoided leading to accurate estimation of parameter intervals. Meanwhile, the establishment of an interval inverse problem is highly simplified, accompanied by a saving of computational costs. By this means a relatively simple and cost-efficient interval updating process can be achieved. Lastly, the feasibility and reliability of the developed method have been verified against a numerical mass–spring system and also against a set of experimentally tested steel plates. Stochastic model updating provides an effective way of handling uncertainties existing in real-world structures. In general, probabilistic theories, fuzzy mathematics or interval analyses are involved in the solution of inverse problems. However in practice, probability distributions or membership functions of structural parameters are often unavailable due to insufficient information of a structure. At this moment an interval model updating procedure shows its superiority in the aspect of problem simplification since only the upper and lower bounds of parameters and responses are sought. To this end, this study develops a new concept of interval response surface models for the purpose of efficiently implementing the interval model updating procedure. The frequent interval overestimation due to the use of interval arithmetic can be maximally avoided leading to accurate estimation of parameter intervals. Meanwhile, the establishment of an interval inverse problem is highly simplified, accompanied by a saving of computational costs. By this means a relatively simple and cost-efficient interval updating process can be achieved. Lastly, the feasibility and reliability of the developed method have been verified against a numerical mass–spring system and also against a set of experimentally tested steel plates. Interval response surface models Elsevier Interval inverse problem Elsevier Interval overestimation. Elsevier Interval model updating Elsevier Interval arithmetic Elsevier Zhang, Qiu-Hu oth Ren, Wei-Xin oth Enthalten in Elsevier Jaroenkietkajorn, Ukrit ELSEVIER Species loss from land use of oil palm plantations in Thailand 2021 mssp Amsterdam [u.a.] (DE-627)ELV007151810 volume:60 year:2015 pages:909-927 extent:19 https://doi.org/10.1016/j.ymssp.2015.01.016 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA AR 60 2015 909-927 19 045F 004 |
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Enthalten in Species loss from land use of oil palm plantations in Thailand Amsterdam [u.a.] volume:60 year:2015 pages:909-927 extent:19 |
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Stochastic model updating provides an effective way of handling uncertainties existing in real-world structures. In general, probabilistic theories, fuzzy mathematics or interval analyses are involved in the solution of inverse problems. However in practice, probability distributions or membership functions of structural parameters are often unavailable due to insufficient information of a structure. At this moment an interval model updating procedure shows its superiority in the aspect of problem simplification since only the upper and lower bounds of parameters and responses are sought. To this end, this study develops a new concept of interval response surface models for the purpose of efficiently implementing the interval model updating procedure. The frequent interval overestimation due to the use of interval arithmetic can be maximally avoided leading to accurate estimation of parameter intervals. Meanwhile, the establishment of an interval inverse problem is highly simplified, accompanied by a saving of computational costs. By this means a relatively simple and cost-efficient interval updating process can be achieved. Lastly, the feasibility and reliability of the developed method have been verified against a numerical mass–spring system and also against a set of experimentally tested steel plates. |
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Stochastic model updating provides an effective way of handling uncertainties existing in real-world structures. In general, probabilistic theories, fuzzy mathematics or interval analyses are involved in the solution of inverse problems. However in practice, probability distributions or membership functions of structural parameters are often unavailable due to insufficient information of a structure. At this moment an interval model updating procedure shows its superiority in the aspect of problem simplification since only the upper and lower bounds of parameters and responses are sought. To this end, this study develops a new concept of interval response surface models for the purpose of efficiently implementing the interval model updating procedure. The frequent interval overestimation due to the use of interval arithmetic can be maximally avoided leading to accurate estimation of parameter intervals. Meanwhile, the establishment of an interval inverse problem is highly simplified, accompanied by a saving of computational costs. By this means a relatively simple and cost-efficient interval updating process can be achieved. Lastly, the feasibility and reliability of the developed method have been verified against a numerical mass–spring system and also against a set of experimentally tested steel plates. |
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Stochastic model updating provides an effective way of handling uncertainties existing in real-world structures. In general, probabilistic theories, fuzzy mathematics or interval analyses are involved in the solution of inverse problems. However in practice, probability distributions or membership functions of structural parameters are often unavailable due to insufficient information of a structure. At this moment an interval model updating procedure shows its superiority in the aspect of problem simplification since only the upper and lower bounds of parameters and responses are sought. To this end, this study develops a new concept of interval response surface models for the purpose of efficiently implementing the interval model updating procedure. The frequent interval overestimation due to the use of interval arithmetic can be maximally avoided leading to accurate estimation of parameter intervals. Meanwhile, the establishment of an interval inverse problem is highly simplified, accompanied by a saving of computational costs. By this means a relatively simple and cost-efficient interval updating process can be achieved. Lastly, the feasibility and reliability of the developed method have been verified against a numerical mass–spring system and also against a set of experimentally tested steel plates. |
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