A novel high level canonical piecewise linear model based on the simplicial partition and its application
The piecewise linear (PWL) model has attracted more and more attention in recent research because it can handle complex nonlinearity while maintaining linearity in local regions. A large number of compact representations for PWL modeling have been introduced, such as hinging hyperplanes and its gene...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Gao, Xiaoyong [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2014transfer abstract |
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| Schlagwörter: |
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| Umfang: |
7 |
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| Übergeordnetes Werk: |
Enthalten in: Selective extraction, structural characterisation and antifungal activity assessment of napins from an industrial rapeseed meal - 2012, the science and engineering of measurement and automation, Amsterdam [u.a.] |
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| Übergeordnetes Werk: |
volume:53 ; year:2014 ; number:5 ; pages:1420-1426 ; extent:7 |
| Links: |
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| DOI / URN: |
10.1016/j.isatra.2013.12.027 |
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ELV023081678 |
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| 520 | |a The piecewise linear (PWL) model has attracted more and more attention in recent research because it can handle complex nonlinearity while maintaining linearity in local regions. A large number of compact representations for PWL modeling have been introduced, such as hinging hyperplanes and its generalized version. However, the existing methods usually give rise to many and complex subregions, which is an issue known as “curse of partitions”, and hampered practical applications of PWL models. In this paper, a novel high level canonical PWL model is presented to tackle the curse of partitions. In more detail, an improved simplicial partition strategy with alterable intervals is proposed to improve the model representation capability. The proposed PWL model guarantees an unchangeable topology during training and thus a limited number of subregions after training. Several numerical experiments, and a simulated chemical process, are used to demonstrate the effectiveness of the proposed model. | ||
| 520 | |a The piecewise linear (PWL) model has attracted more and more attention in recent research because it can handle complex nonlinearity while maintaining linearity in local regions. A large number of compact representations for PWL modeling have been introduced, such as hinging hyperplanes and its generalized version. However, the existing methods usually give rise to many and complex subregions, which is an issue known as “curse of partitions”, and hampered practical applications of PWL models. In this paper, a novel high level canonical PWL model is presented to tackle the curse of partitions. In more detail, an improved simplicial partition strategy with alterable intervals is proposed to improve the model representation capability. The proposed PWL model guarantees an unchangeable topology during training and thus a limited number of subregions after training. Several numerical experiments, and a simulated chemical process, are used to demonstrate the effectiveness of the proposed model. | ||
| 650 | 7 | |a Piecewise linear |2 Elsevier | |
| 650 | 7 | |a Simplicial partition |2 Elsevier | |
| 650 | 7 | |a Process model |2 Elsevier | |
| 700 | 1 | |a Jiang, Yongheng |4 oth | |
| 700 | 1 | |a Huang, Dexian |4 oth | |
| 700 | 1 | |a Xiong, Zhihua |4 oth | |
| 773 | 0 | 8 | |i Enthalten in |n Elsevier |t Selective extraction, structural characterisation and antifungal activity assessment of napins from an industrial rapeseed meal |d 2012 |d the science and engineering of measurement and automation |g Amsterdam [u.a.] |w (DE-627)ELV011067004 |
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10.1016/j.isatra.2013.12.027 doi GBVA2014021000003.pica (DE-627)ELV023081678 (ELSEVIER)S0019-0578(13)00237-1 DE-627 ger DE-627 rakwb eng 530 530 DE-600 540 VZ 660 VZ 540 VZ 35.00 bkl Gao, Xiaoyong verfasserin aut A novel high level canonical piecewise linear model based on the simplicial partition and its application 2014transfer abstract 7 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The piecewise linear (PWL) model has attracted more and more attention in recent research because it can handle complex nonlinearity while maintaining linearity in local regions. A large number of compact representations for PWL modeling have been introduced, such as hinging hyperplanes and its generalized version. However, the existing methods usually give rise to many and complex subregions, which is an issue known as “curse of partitions”, and hampered practical applications of PWL models. In this paper, a novel high level canonical PWL model is presented to tackle the curse of partitions. In more detail, an improved simplicial partition strategy with alterable intervals is proposed to improve the model representation capability. The proposed PWL model guarantees an unchangeable topology during training and thus a limited number of subregions after training. Several numerical experiments, and a simulated chemical process, are used to demonstrate the effectiveness of the proposed model. The piecewise linear (PWL) model has attracted more and more attention in recent research because it can handle complex nonlinearity while maintaining linearity in local regions. A large number of compact representations for PWL modeling have been introduced, such as hinging hyperplanes and its generalized version. However, the existing methods usually give rise to many and complex subregions, which is an issue known as “curse of partitions”, and hampered practical applications of PWL models. In this paper, a novel high level canonical PWL model is presented to tackle the curse of partitions. In more detail, an improved simplicial partition strategy with alterable intervals is proposed to improve the model representation capability. The proposed PWL model guarantees an unchangeable topology during training and thus a limited number of subregions after training. Several numerical experiments, and a simulated chemical process, are used to demonstrate the effectiveness of the proposed model. Piecewise linear Elsevier Simplicial partition Elsevier Process model Elsevier Jiang, Yongheng oth Huang, Dexian oth Xiong, Zhihua oth Enthalten in Elsevier Selective extraction, structural characterisation and antifungal activity assessment of napins from an industrial rapeseed meal 2012 the science and engineering of measurement and automation Amsterdam [u.a.] (DE-627)ELV011067004 volume:53 year:2014 number:5 pages:1420-1426 extent:7 https://doi.org/10.1016/j.isatra.2013.12.027 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_22 GBV_ILN_40 GBV_ILN_105 35.00 Chemie: Allgemeines VZ AR 53 2014 5 1420-1426 7 045F 530 |
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10.1016/j.isatra.2013.12.027 doi GBVA2014021000003.pica (DE-627)ELV023081678 (ELSEVIER)S0019-0578(13)00237-1 DE-627 ger DE-627 rakwb eng 530 530 DE-600 540 VZ 660 VZ 540 VZ 35.00 bkl Gao, Xiaoyong verfasserin aut A novel high level canonical piecewise linear model based on the simplicial partition and its application 2014transfer abstract 7 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The piecewise linear (PWL) model has attracted more and more attention in recent research because it can handle complex nonlinearity while maintaining linearity in local regions. A large number of compact representations for PWL modeling have been introduced, such as hinging hyperplanes and its generalized version. However, the existing methods usually give rise to many and complex subregions, which is an issue known as “curse of partitions”, and hampered practical applications of PWL models. In this paper, a novel high level canonical PWL model is presented to tackle the curse of partitions. In more detail, an improved simplicial partition strategy with alterable intervals is proposed to improve the model representation capability. The proposed PWL model guarantees an unchangeable topology during training and thus a limited number of subregions after training. Several numerical experiments, and a simulated chemical process, are used to demonstrate the effectiveness of the proposed model. The piecewise linear (PWL) model has attracted more and more attention in recent research because it can handle complex nonlinearity while maintaining linearity in local regions. A large number of compact representations for PWL modeling have been introduced, such as hinging hyperplanes and its generalized version. However, the existing methods usually give rise to many and complex subregions, which is an issue known as “curse of partitions”, and hampered practical applications of PWL models. In this paper, a novel high level canonical PWL model is presented to tackle the curse of partitions. In more detail, an improved simplicial partition strategy with alterable intervals is proposed to improve the model representation capability. The proposed PWL model guarantees an unchangeable topology during training and thus a limited number of subregions after training. Several numerical experiments, and a simulated chemical process, are used to demonstrate the effectiveness of the proposed model. Piecewise linear Elsevier Simplicial partition Elsevier Process model Elsevier Jiang, Yongheng oth Huang, Dexian oth Xiong, Zhihua oth Enthalten in Elsevier Selective extraction, structural characterisation and antifungal activity assessment of napins from an industrial rapeseed meal 2012 the science and engineering of measurement and automation Amsterdam [u.a.] (DE-627)ELV011067004 volume:53 year:2014 number:5 pages:1420-1426 extent:7 https://doi.org/10.1016/j.isatra.2013.12.027 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_22 GBV_ILN_40 GBV_ILN_105 35.00 Chemie: Allgemeines VZ AR 53 2014 5 1420-1426 7 045F 530 |
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10.1016/j.isatra.2013.12.027 doi GBVA2014021000003.pica (DE-627)ELV023081678 (ELSEVIER)S0019-0578(13)00237-1 DE-627 ger DE-627 rakwb eng 530 530 DE-600 540 VZ 660 VZ 540 VZ 35.00 bkl Gao, Xiaoyong verfasserin aut A novel high level canonical piecewise linear model based on the simplicial partition and its application 2014transfer abstract 7 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The piecewise linear (PWL) model has attracted more and more attention in recent research because it can handle complex nonlinearity while maintaining linearity in local regions. A large number of compact representations for PWL modeling have been introduced, such as hinging hyperplanes and its generalized version. However, the existing methods usually give rise to many and complex subregions, which is an issue known as “curse of partitions”, and hampered practical applications of PWL models. In this paper, a novel high level canonical PWL model is presented to tackle the curse of partitions. In more detail, an improved simplicial partition strategy with alterable intervals is proposed to improve the model representation capability. The proposed PWL model guarantees an unchangeable topology during training and thus a limited number of subregions after training. Several numerical experiments, and a simulated chemical process, are used to demonstrate the effectiveness of the proposed model. The piecewise linear (PWL) model has attracted more and more attention in recent research because it can handle complex nonlinearity while maintaining linearity in local regions. A large number of compact representations for PWL modeling have been introduced, such as hinging hyperplanes and its generalized version. However, the existing methods usually give rise to many and complex subregions, which is an issue known as “curse of partitions”, and hampered practical applications of PWL models. In this paper, a novel high level canonical PWL model is presented to tackle the curse of partitions. In more detail, an improved simplicial partition strategy with alterable intervals is proposed to improve the model representation capability. The proposed PWL model guarantees an unchangeable topology during training and thus a limited number of subregions after training. Several numerical experiments, and a simulated chemical process, are used to demonstrate the effectiveness of the proposed model. Piecewise linear Elsevier Simplicial partition Elsevier Process model Elsevier Jiang, Yongheng oth Huang, Dexian oth Xiong, Zhihua oth Enthalten in Elsevier Selective extraction, structural characterisation and antifungal activity assessment of napins from an industrial rapeseed meal 2012 the science and engineering of measurement and automation Amsterdam [u.a.] (DE-627)ELV011067004 volume:53 year:2014 number:5 pages:1420-1426 extent:7 https://doi.org/10.1016/j.isatra.2013.12.027 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_22 GBV_ILN_40 GBV_ILN_105 35.00 Chemie: Allgemeines VZ AR 53 2014 5 1420-1426 7 045F 530 |
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10.1016/j.isatra.2013.12.027 doi GBVA2014021000003.pica (DE-627)ELV023081678 (ELSEVIER)S0019-0578(13)00237-1 DE-627 ger DE-627 rakwb eng 530 530 DE-600 540 VZ 660 VZ 540 VZ 35.00 bkl Gao, Xiaoyong verfasserin aut A novel high level canonical piecewise linear model based on the simplicial partition and its application 2014transfer abstract 7 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The piecewise linear (PWL) model has attracted more and more attention in recent research because it can handle complex nonlinearity while maintaining linearity in local regions. A large number of compact representations for PWL modeling have been introduced, such as hinging hyperplanes and its generalized version. However, the existing methods usually give rise to many and complex subregions, which is an issue known as “curse of partitions”, and hampered practical applications of PWL models. In this paper, a novel high level canonical PWL model is presented to tackle the curse of partitions. In more detail, an improved simplicial partition strategy with alterable intervals is proposed to improve the model representation capability. The proposed PWL model guarantees an unchangeable topology during training and thus a limited number of subregions after training. Several numerical experiments, and a simulated chemical process, are used to demonstrate the effectiveness of the proposed model. The piecewise linear (PWL) model has attracted more and more attention in recent research because it can handle complex nonlinearity while maintaining linearity in local regions. A large number of compact representations for PWL modeling have been introduced, such as hinging hyperplanes and its generalized version. However, the existing methods usually give rise to many and complex subregions, which is an issue known as “curse of partitions”, and hampered practical applications of PWL models. In this paper, a novel high level canonical PWL model is presented to tackle the curse of partitions. In more detail, an improved simplicial partition strategy with alterable intervals is proposed to improve the model representation capability. The proposed PWL model guarantees an unchangeable topology during training and thus a limited number of subregions after training. Several numerical experiments, and a simulated chemical process, are used to demonstrate the effectiveness of the proposed model. Piecewise linear Elsevier Simplicial partition Elsevier Process model Elsevier Jiang, Yongheng oth Huang, Dexian oth Xiong, Zhihua oth Enthalten in Elsevier Selective extraction, structural characterisation and antifungal activity assessment of napins from an industrial rapeseed meal 2012 the science and engineering of measurement and automation Amsterdam [u.a.] (DE-627)ELV011067004 volume:53 year:2014 number:5 pages:1420-1426 extent:7 https://doi.org/10.1016/j.isatra.2013.12.027 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_22 GBV_ILN_40 GBV_ILN_105 35.00 Chemie: Allgemeines VZ AR 53 2014 5 1420-1426 7 045F 530 |
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10.1016/j.isatra.2013.12.027 doi GBVA2014021000003.pica (DE-627)ELV023081678 (ELSEVIER)S0019-0578(13)00237-1 DE-627 ger DE-627 rakwb eng 530 530 DE-600 540 VZ 660 VZ 540 VZ 35.00 bkl Gao, Xiaoyong verfasserin aut A novel high level canonical piecewise linear model based on the simplicial partition and its application 2014transfer abstract 7 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The piecewise linear (PWL) model has attracted more and more attention in recent research because it can handle complex nonlinearity while maintaining linearity in local regions. A large number of compact representations for PWL modeling have been introduced, such as hinging hyperplanes and its generalized version. However, the existing methods usually give rise to many and complex subregions, which is an issue known as “curse of partitions”, and hampered practical applications of PWL models. In this paper, a novel high level canonical PWL model is presented to tackle the curse of partitions. In more detail, an improved simplicial partition strategy with alterable intervals is proposed to improve the model representation capability. The proposed PWL model guarantees an unchangeable topology during training and thus a limited number of subregions after training. Several numerical experiments, and a simulated chemical process, are used to demonstrate the effectiveness of the proposed model. The piecewise linear (PWL) model has attracted more and more attention in recent research because it can handle complex nonlinearity while maintaining linearity in local regions. A large number of compact representations for PWL modeling have been introduced, such as hinging hyperplanes and its generalized version. However, the existing methods usually give rise to many and complex subregions, which is an issue known as “curse of partitions”, and hampered practical applications of PWL models. In this paper, a novel high level canonical PWL model is presented to tackle the curse of partitions. In more detail, an improved simplicial partition strategy with alterable intervals is proposed to improve the model representation capability. The proposed PWL model guarantees an unchangeable topology during training and thus a limited number of subregions after training. Several numerical experiments, and a simulated chemical process, are used to demonstrate the effectiveness of the proposed model. Piecewise linear Elsevier Simplicial partition Elsevier Process model Elsevier Jiang, Yongheng oth Huang, Dexian oth Xiong, Zhihua oth Enthalten in Elsevier Selective extraction, structural characterisation and antifungal activity assessment of napins from an industrial rapeseed meal 2012 the science and engineering of measurement and automation Amsterdam [u.a.] (DE-627)ELV011067004 volume:53 year:2014 number:5 pages:1420-1426 extent:7 https://doi.org/10.1016/j.isatra.2013.12.027 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_22 GBV_ILN_40 GBV_ILN_105 35.00 Chemie: Allgemeines VZ AR 53 2014 5 1420-1426 7 045F 530 |
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Selective extraction, structural characterisation and antifungal activity assessment of napins from an industrial rapeseed meal |
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A novel high level canonical piecewise linear model based on the simplicial partition and its application |
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The piecewise linear (PWL) model has attracted more and more attention in recent research because it can handle complex nonlinearity while maintaining linearity in local regions. A large number of compact representations for PWL modeling have been introduced, such as hinging hyperplanes and its generalized version. However, the existing methods usually give rise to many and complex subregions, which is an issue known as “curse of partitions”, and hampered practical applications of PWL models. In this paper, a novel high level canonical PWL model is presented to tackle the curse of partitions. In more detail, an improved simplicial partition strategy with alterable intervals is proposed to improve the model representation capability. The proposed PWL model guarantees an unchangeable topology during training and thus a limited number of subregions after training. Several numerical experiments, and a simulated chemical process, are used to demonstrate the effectiveness of the proposed model. |
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The piecewise linear (PWL) model has attracted more and more attention in recent research because it can handle complex nonlinearity while maintaining linearity in local regions. A large number of compact representations for PWL modeling have been introduced, such as hinging hyperplanes and its generalized version. However, the existing methods usually give rise to many and complex subregions, which is an issue known as “curse of partitions”, and hampered practical applications of PWL models. In this paper, a novel high level canonical PWL model is presented to tackle the curse of partitions. In more detail, an improved simplicial partition strategy with alterable intervals is proposed to improve the model representation capability. The proposed PWL model guarantees an unchangeable topology during training and thus a limited number of subregions after training. Several numerical experiments, and a simulated chemical process, are used to demonstrate the effectiveness of the proposed model. |
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The piecewise linear (PWL) model has attracted more and more attention in recent research because it can handle complex nonlinearity while maintaining linearity in local regions. A large number of compact representations for PWL modeling have been introduced, such as hinging hyperplanes and its generalized version. However, the existing methods usually give rise to many and complex subregions, which is an issue known as “curse of partitions”, and hampered practical applications of PWL models. In this paper, a novel high level canonical PWL model is presented to tackle the curse of partitions. In more detail, an improved simplicial partition strategy with alterable intervals is proposed to improve the model representation capability. The proposed PWL model guarantees an unchangeable topology during training and thus a limited number of subregions after training. Several numerical experiments, and a simulated chemical process, are used to demonstrate the effectiveness of the proposed model. |
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