RETRACTED ARTICLE:Rock stress and deformation characteristics based on SVM and sports high-intensity interval training
Abstract Since the 21st century, with the rapid development of China’s domestic economy and the continuous improvement of people’s living standards, the development and construction of urban infrastructure are also faster and faster, and the requirements for the stability of foundations such as buil...
Ausführliche Beschreibung
Autor*in: |
Ziyu, Liu [verfasserIn] Qingyao, Sun [verfasserIn] |
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Format: |
E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2021 |
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Schlagwörter: |
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Anmerkung: |
© Saudi Society for Geosciences 2021 |
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Übergeordnetes Werk: |
Enthalten in: Arabian journal of geosciences - Berlin : Springer, 2008, 14(2021), 17 vom: 17. Aug. |
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Übergeordnetes Werk: |
volume:14 ; year:2021 ; number:17 ; day:17 ; month:08 |
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DOI / URN: |
10.1007/s12517-021-07944-0 |
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Katalog-ID: |
SPR044856806 |
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520 | |a Abstract Since the 21st century, with the rapid development of China’s domestic economy and the continuous improvement of people’s living standards, the development and construction of urban infrastructure are also faster and faster, and the requirements for the stability of foundations such as buildings, roads and bridges, subway, and high-speed railway are also higher and higher. In the southwest of China, due to the influence of terrain conditions, there are a large number of soil rock mixtures with uneven particle size change and complex particle composition. Understanding the mechanical properties of soil rock mixture and effectively measuring the strength and deformation parameters of soil rock mixture are one of the most important research topics. At the same time, in order to identify the soil rock mixture, the conventional Gauss Euclidean distance calculation method cannot fully reflect the structure of soil rock mixture, so an improved Gauss kernel function multiclass support vector machine (MSVM) method is proposed. On the basis of Gaussian radial, Gaussian kernel function is used to replace Euclidean distance in ranging. The attitude kernel function of Gaussian kernel function is established according to ranging. Many types of support vector machines (SVM) are constructed by a binary tree method to complete classification. The experimental results show that, based on the improved Gaussian kernel function, this paper discusses the high-intensity interval training, so as to achieve a good recognition effect, whether it has a promoting effect on improving the physical quality of college boys, and designs the training scheme to carry out experimental intervention on college boys, so as to provide a new training theoretical reference for school physical education teaching. It also provides a training method for college boys to improve their physical fitness. | ||
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10.1007/s12517-021-07944-0 doi (DE-627)SPR044856806 (SPR)s12517-021-07944-0-e DE-627 ger DE-627 rakwb eng 550 ASE Ziyu, Liu verfasserin aut RETRACTED ARTICLE:Rock stress and deformation characteristics based on SVM and sports high-intensity interval training 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Saudi Society for Geosciences 2021 Abstract Since the 21st century, with the rapid development of China’s domestic economy and the continuous improvement of people’s living standards, the development and construction of urban infrastructure are also faster and faster, and the requirements for the stability of foundations such as buildings, roads and bridges, subway, and high-speed railway are also higher and higher. In the southwest of China, due to the influence of terrain conditions, there are a large number of soil rock mixtures with uneven particle size change and complex particle composition. Understanding the mechanical properties of soil rock mixture and effectively measuring the strength and deformation parameters of soil rock mixture are one of the most important research topics. At the same time, in order to identify the soil rock mixture, the conventional Gauss Euclidean distance calculation method cannot fully reflect the structure of soil rock mixture, so an improved Gauss kernel function multiclass support vector machine (MSVM) method is proposed. On the basis of Gaussian radial, Gaussian kernel function is used to replace Euclidean distance in ranging. The attitude kernel function of Gaussian kernel function is established according to ranging. Many types of support vector machines (SVM) are constructed by a binary tree method to complete classification. The experimental results show that, based on the improved Gaussian kernel function, this paper discusses the high-intensity interval training, so as to achieve a good recognition effect, whether it has a promoting effect on improving the physical quality of college boys, and designs the training scheme to carry out experimental intervention on college boys, so as to provide a new training theoretical reference for school physical education teaching. It also provides a training method for college boys to improve their physical fitness. Improved Gaussian kernel function (dpeaa)DE-He213 Soil rock mixture (dpeaa)DE-He213 College student (dpeaa)DE-He213 Optimization of physical training (dpeaa)DE-He213 Qingyao, Sun verfasserin aut Enthalten in Arabian journal of geosciences Berlin : Springer, 2008 14(2021), 17 vom: 17. Aug. (DE-627)572421877 (DE-600)2438771-X 1866-7538 nnns volume:14 year:2021 number:17 day:17 month:08 https://dx.doi.org/10.1007/s12517-021-07944-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 14 2021 17 17 08 |
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10.1007/s12517-021-07944-0 doi (DE-627)SPR044856806 (SPR)s12517-021-07944-0-e DE-627 ger DE-627 rakwb eng 550 ASE Ziyu, Liu verfasserin aut RETRACTED ARTICLE:Rock stress and deformation characteristics based on SVM and sports high-intensity interval training 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Saudi Society for Geosciences 2021 Abstract Since the 21st century, with the rapid development of China’s domestic economy and the continuous improvement of people’s living standards, the development and construction of urban infrastructure are also faster and faster, and the requirements for the stability of foundations such as buildings, roads and bridges, subway, and high-speed railway are also higher and higher. In the southwest of China, due to the influence of terrain conditions, there are a large number of soil rock mixtures with uneven particle size change and complex particle composition. Understanding the mechanical properties of soil rock mixture and effectively measuring the strength and deformation parameters of soil rock mixture are one of the most important research topics. At the same time, in order to identify the soil rock mixture, the conventional Gauss Euclidean distance calculation method cannot fully reflect the structure of soil rock mixture, so an improved Gauss kernel function multiclass support vector machine (MSVM) method is proposed. On the basis of Gaussian radial, Gaussian kernel function is used to replace Euclidean distance in ranging. The attitude kernel function of Gaussian kernel function is established according to ranging. Many types of support vector machines (SVM) are constructed by a binary tree method to complete classification. The experimental results show that, based on the improved Gaussian kernel function, this paper discusses the high-intensity interval training, so as to achieve a good recognition effect, whether it has a promoting effect on improving the physical quality of college boys, and designs the training scheme to carry out experimental intervention on college boys, so as to provide a new training theoretical reference for school physical education teaching. It also provides a training method for college boys to improve their physical fitness. Improved Gaussian kernel function (dpeaa)DE-He213 Soil rock mixture (dpeaa)DE-He213 College student (dpeaa)DE-He213 Optimization of physical training (dpeaa)DE-He213 Qingyao, Sun verfasserin aut Enthalten in Arabian journal of geosciences Berlin : Springer, 2008 14(2021), 17 vom: 17. Aug. (DE-627)572421877 (DE-600)2438771-X 1866-7538 nnns volume:14 year:2021 number:17 day:17 month:08 https://dx.doi.org/10.1007/s12517-021-07944-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 14 2021 17 17 08 |
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10.1007/s12517-021-07944-0 doi (DE-627)SPR044856806 (SPR)s12517-021-07944-0-e DE-627 ger DE-627 rakwb eng 550 ASE Ziyu, Liu verfasserin aut RETRACTED ARTICLE:Rock stress and deformation characteristics based on SVM and sports high-intensity interval training 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Saudi Society for Geosciences 2021 Abstract Since the 21st century, with the rapid development of China’s domestic economy and the continuous improvement of people’s living standards, the development and construction of urban infrastructure are also faster and faster, and the requirements for the stability of foundations such as buildings, roads and bridges, subway, and high-speed railway are also higher and higher. In the southwest of China, due to the influence of terrain conditions, there are a large number of soil rock mixtures with uneven particle size change and complex particle composition. Understanding the mechanical properties of soil rock mixture and effectively measuring the strength and deformation parameters of soil rock mixture are one of the most important research topics. At the same time, in order to identify the soil rock mixture, the conventional Gauss Euclidean distance calculation method cannot fully reflect the structure of soil rock mixture, so an improved Gauss kernel function multiclass support vector machine (MSVM) method is proposed. On the basis of Gaussian radial, Gaussian kernel function is used to replace Euclidean distance in ranging. The attitude kernel function of Gaussian kernel function is established according to ranging. Many types of support vector machines (SVM) are constructed by a binary tree method to complete classification. The experimental results show that, based on the improved Gaussian kernel function, this paper discusses the high-intensity interval training, so as to achieve a good recognition effect, whether it has a promoting effect on improving the physical quality of college boys, and designs the training scheme to carry out experimental intervention on college boys, so as to provide a new training theoretical reference for school physical education teaching. It also provides a training method for college boys to improve their physical fitness. Improved Gaussian kernel function (dpeaa)DE-He213 Soil rock mixture (dpeaa)DE-He213 College student (dpeaa)DE-He213 Optimization of physical training (dpeaa)DE-He213 Qingyao, Sun verfasserin aut Enthalten in Arabian journal of geosciences Berlin : Springer, 2008 14(2021), 17 vom: 17. Aug. (DE-627)572421877 (DE-600)2438771-X 1866-7538 nnns volume:14 year:2021 number:17 day:17 month:08 https://dx.doi.org/10.1007/s12517-021-07944-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 14 2021 17 17 08 |
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10.1007/s12517-021-07944-0 doi (DE-627)SPR044856806 (SPR)s12517-021-07944-0-e DE-627 ger DE-627 rakwb eng 550 ASE Ziyu, Liu verfasserin aut RETRACTED ARTICLE:Rock stress and deformation characteristics based on SVM and sports high-intensity interval training 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Saudi Society for Geosciences 2021 Abstract Since the 21st century, with the rapid development of China’s domestic economy and the continuous improvement of people’s living standards, the development and construction of urban infrastructure are also faster and faster, and the requirements for the stability of foundations such as buildings, roads and bridges, subway, and high-speed railway are also higher and higher. In the southwest of China, due to the influence of terrain conditions, there are a large number of soil rock mixtures with uneven particle size change and complex particle composition. Understanding the mechanical properties of soil rock mixture and effectively measuring the strength and deformation parameters of soil rock mixture are one of the most important research topics. At the same time, in order to identify the soil rock mixture, the conventional Gauss Euclidean distance calculation method cannot fully reflect the structure of soil rock mixture, so an improved Gauss kernel function multiclass support vector machine (MSVM) method is proposed. On the basis of Gaussian radial, Gaussian kernel function is used to replace Euclidean distance in ranging. The attitude kernel function of Gaussian kernel function is established according to ranging. Many types of support vector machines (SVM) are constructed by a binary tree method to complete classification. The experimental results show that, based on the improved Gaussian kernel function, this paper discusses the high-intensity interval training, so as to achieve a good recognition effect, whether it has a promoting effect on improving the physical quality of college boys, and designs the training scheme to carry out experimental intervention on college boys, so as to provide a new training theoretical reference for school physical education teaching. It also provides a training method for college boys to improve their physical fitness. Improved Gaussian kernel function (dpeaa)DE-He213 Soil rock mixture (dpeaa)DE-He213 College student (dpeaa)DE-He213 Optimization of physical training (dpeaa)DE-He213 Qingyao, Sun verfasserin aut Enthalten in Arabian journal of geosciences Berlin : Springer, 2008 14(2021), 17 vom: 17. Aug. (DE-627)572421877 (DE-600)2438771-X 1866-7538 nnns volume:14 year:2021 number:17 day:17 month:08 https://dx.doi.org/10.1007/s12517-021-07944-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 14 2021 17 17 08 |
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10.1007/s12517-021-07944-0 doi (DE-627)SPR044856806 (SPR)s12517-021-07944-0-e DE-627 ger DE-627 rakwb eng 550 ASE Ziyu, Liu verfasserin aut RETRACTED ARTICLE:Rock stress and deformation characteristics based on SVM and sports high-intensity interval training 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Saudi Society for Geosciences 2021 Abstract Since the 21st century, with the rapid development of China’s domestic economy and the continuous improvement of people’s living standards, the development and construction of urban infrastructure are also faster and faster, and the requirements for the stability of foundations such as buildings, roads and bridges, subway, and high-speed railway are also higher and higher. In the southwest of China, due to the influence of terrain conditions, there are a large number of soil rock mixtures with uneven particle size change and complex particle composition. Understanding the mechanical properties of soil rock mixture and effectively measuring the strength and deformation parameters of soil rock mixture are one of the most important research topics. At the same time, in order to identify the soil rock mixture, the conventional Gauss Euclidean distance calculation method cannot fully reflect the structure of soil rock mixture, so an improved Gauss kernel function multiclass support vector machine (MSVM) method is proposed. On the basis of Gaussian radial, Gaussian kernel function is used to replace Euclidean distance in ranging. The attitude kernel function of Gaussian kernel function is established according to ranging. Many types of support vector machines (SVM) are constructed by a binary tree method to complete classification. The experimental results show that, based on the improved Gaussian kernel function, this paper discusses the high-intensity interval training, so as to achieve a good recognition effect, whether it has a promoting effect on improving the physical quality of college boys, and designs the training scheme to carry out experimental intervention on college boys, so as to provide a new training theoretical reference for school physical education teaching. It also provides a training method for college boys to improve their physical fitness. Improved Gaussian kernel function (dpeaa)DE-He213 Soil rock mixture (dpeaa)DE-He213 College student (dpeaa)DE-He213 Optimization of physical training (dpeaa)DE-He213 Qingyao, Sun verfasserin aut Enthalten in Arabian journal of geosciences Berlin : Springer, 2008 14(2021), 17 vom: 17. Aug. (DE-627)572421877 (DE-600)2438771-X 1866-7538 nnns volume:14 year:2021 number:17 day:17 month:08 https://dx.doi.org/10.1007/s12517-021-07944-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 14 2021 17 17 08 |
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In the southwest of China, due to the influence of terrain conditions, there are a large number of soil rock mixtures with uneven particle size change and complex particle composition. Understanding the mechanical properties of soil rock mixture and effectively measuring the strength and deformation parameters of soil rock mixture are one of the most important research topics. At the same time, in order to identify the soil rock mixture, the conventional Gauss Euclidean distance calculation method cannot fully reflect the structure of soil rock mixture, so an improved Gauss kernel function multiclass support vector machine (MSVM) method is proposed. On the basis of Gaussian radial, Gaussian kernel function is used to replace Euclidean distance in ranging. The attitude kernel function of Gaussian kernel function is established according to ranging. Many types of support vector machines (SVM) are constructed by a binary tree method to complete classification. 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Ziyu, Liu |
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Ziyu, Liu ddc 550 misc Improved Gaussian kernel function misc Soil rock mixture misc College student misc Optimization of physical training RETRACTED ARTICLE:Rock stress and deformation characteristics based on SVM and sports high-intensity interval training |
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retracted article:rock stress and deformation characteristics based on svm and sports high-intensity interval training |
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RETRACTED ARTICLE:Rock stress and deformation characteristics based on SVM and sports high-intensity interval training |
abstract |
Abstract Since the 21st century, with the rapid development of China’s domestic economy and the continuous improvement of people’s living standards, the development and construction of urban infrastructure are also faster and faster, and the requirements for the stability of foundations such as buildings, roads and bridges, subway, and high-speed railway are also higher and higher. In the southwest of China, due to the influence of terrain conditions, there are a large number of soil rock mixtures with uneven particle size change and complex particle composition. Understanding the mechanical properties of soil rock mixture and effectively measuring the strength and deformation parameters of soil rock mixture are one of the most important research topics. At the same time, in order to identify the soil rock mixture, the conventional Gauss Euclidean distance calculation method cannot fully reflect the structure of soil rock mixture, so an improved Gauss kernel function multiclass support vector machine (MSVM) method is proposed. On the basis of Gaussian radial, Gaussian kernel function is used to replace Euclidean distance in ranging. The attitude kernel function of Gaussian kernel function is established according to ranging. Many types of support vector machines (SVM) are constructed by a binary tree method to complete classification. The experimental results show that, based on the improved Gaussian kernel function, this paper discusses the high-intensity interval training, so as to achieve a good recognition effect, whether it has a promoting effect on improving the physical quality of college boys, and designs the training scheme to carry out experimental intervention on college boys, so as to provide a new training theoretical reference for school physical education teaching. It also provides a training method for college boys to improve their physical fitness. © Saudi Society for Geosciences 2021 |
abstractGer |
Abstract Since the 21st century, with the rapid development of China’s domestic economy and the continuous improvement of people’s living standards, the development and construction of urban infrastructure are also faster and faster, and the requirements for the stability of foundations such as buildings, roads and bridges, subway, and high-speed railway are also higher and higher. In the southwest of China, due to the influence of terrain conditions, there are a large number of soil rock mixtures with uneven particle size change and complex particle composition. Understanding the mechanical properties of soil rock mixture and effectively measuring the strength and deformation parameters of soil rock mixture are one of the most important research topics. At the same time, in order to identify the soil rock mixture, the conventional Gauss Euclidean distance calculation method cannot fully reflect the structure of soil rock mixture, so an improved Gauss kernel function multiclass support vector machine (MSVM) method is proposed. On the basis of Gaussian radial, Gaussian kernel function is used to replace Euclidean distance in ranging. The attitude kernel function of Gaussian kernel function is established according to ranging. Many types of support vector machines (SVM) are constructed by a binary tree method to complete classification. The experimental results show that, based on the improved Gaussian kernel function, this paper discusses the high-intensity interval training, so as to achieve a good recognition effect, whether it has a promoting effect on improving the physical quality of college boys, and designs the training scheme to carry out experimental intervention on college boys, so as to provide a new training theoretical reference for school physical education teaching. It also provides a training method for college boys to improve their physical fitness. © Saudi Society for Geosciences 2021 |
abstract_unstemmed |
Abstract Since the 21st century, with the rapid development of China’s domestic economy and the continuous improvement of people’s living standards, the development and construction of urban infrastructure are also faster and faster, and the requirements for the stability of foundations such as buildings, roads and bridges, subway, and high-speed railway are also higher and higher. In the southwest of China, due to the influence of terrain conditions, there are a large number of soil rock mixtures with uneven particle size change and complex particle composition. Understanding the mechanical properties of soil rock mixture and effectively measuring the strength and deformation parameters of soil rock mixture are one of the most important research topics. At the same time, in order to identify the soil rock mixture, the conventional Gauss Euclidean distance calculation method cannot fully reflect the structure of soil rock mixture, so an improved Gauss kernel function multiclass support vector machine (MSVM) method is proposed. On the basis of Gaussian radial, Gaussian kernel function is used to replace Euclidean distance in ranging. The attitude kernel function of Gaussian kernel function is established according to ranging. Many types of support vector machines (SVM) are constructed by a binary tree method to complete classification. The experimental results show that, based on the improved Gaussian kernel function, this paper discusses the high-intensity interval training, so as to achieve a good recognition effect, whether it has a promoting effect on improving the physical quality of college boys, and designs the training scheme to carry out experimental intervention on college boys, so as to provide a new training theoretical reference for school physical education teaching. It also provides a training method for college boys to improve their physical fitness. © Saudi Society for Geosciences 2021 |
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17 |
title_short |
RETRACTED ARTICLE:Rock stress and deformation characteristics based on SVM and sports high-intensity interval training |
url |
https://dx.doi.org/10.1007/s12517-021-07944-0 |
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Qingyao, Sun |
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10.1007/s12517-021-07944-0 |
up_date |
2024-07-04T02:35:57.696Z |
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score |
7.3972845 |