A soft Lasso model for the motion of a ball falling in the non-Newtonian fluid

From the mesoscopic point of view, a new concept of soft matching is proposed innovatively. Then a soft Lasso’s approach to learn the soft dynamical equation for the physical mechanical relationship is proposed, too. Furthermore, a discrete iterative algorithm combining the Newton–Stokes term and th...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Wu, Zongmin [verfasserIn] Yang, Ran [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2024

Schlagwörter:	Soft Lasso Non-Newtonian fluid Data-driven modeling Algebraic differential equation

Übergeordnetes Werk:	Enthalten in: No title available - 131
Übergeordnetes Werk:	volume:131

DOI / URN:	10.1016/j.cnsns.2024.107829

Katalog-ID:	ELV067147402

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245	1	0	\|a A soft Lasso model for the motion of a ball falling in the non-Newtonian fluid
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520			\|a From the mesoscopic point of view, a new concept of soft matching is proposed innovatively. Then a soft Lasso’s approach to learn the soft dynamical equation for the physical mechanical relationship is proposed, too. Furthermore, a discrete iterative algorithm combining the Newton–Stokes term and the soft Lasso’s term is developed to simulate the motion of a ball falling in non-Newtonian fluids. The theory is validated by numerical examples and shows satisfactory results, which exhibit the chaotic phenomena, occasional sudden accelerations and continual random oscillations. These behaviors will maintain for a long time. Furthermore, the pattern of the motion is independent of the initial values as the solution to the Newton–Stokes equation. We find the soft relation in physics to characterize the chaotic phenomena based on the learning method, and improve the method of adding a simple random walk or normal distribution.
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allfields	10.1016/j.cnsns.2024.107829 doi (DE-627)ELV067147402 (ELSEVIER)S1007-5704(24)00015-7 DE-627 ger DE-627 rda eng Wu, Zongmin verfasserin aut A soft Lasso model for the motion of a ball falling in the non-Newtonian fluid 2024 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier From the mesoscopic point of view, a new concept of soft matching is proposed innovatively. Then a soft Lasso’s approach to learn the soft dynamical equation for the physical mechanical relationship is proposed, too. Furthermore, a discrete iterative algorithm combining the Newton–Stokes term and the soft Lasso’s term is developed to simulate the motion of a ball falling in non-Newtonian fluids. The theory is validated by numerical examples and shows satisfactory results, which exhibit the chaotic phenomena, occasional sudden accelerations and continual random oscillations. These behaviors will maintain for a long time. Furthermore, the pattern of the motion is independent of the initial values as the solution to the Newton–Stokes equation. We find the soft relation in physics to characterize the chaotic phenomena based on the learning method, and improve the method of adding a simple random walk or normal distribution. Soft Lasso Non-Newtonian fluid Data-driven modeling Algebraic differential equation Yang, Ran verfasserin (orcid)0000-0001-6129-7547 aut Enthalten in No title available 131 (DE-627)352827580 1007-5704 nnns volume:131 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 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_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 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_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 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_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 131
spelling	10.1016/j.cnsns.2024.107829 doi (DE-627)ELV067147402 (ELSEVIER)S1007-5704(24)00015-7 DE-627 ger DE-627 rda eng Wu, Zongmin verfasserin aut A soft Lasso model for the motion of a ball falling in the non-Newtonian fluid 2024 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier From the mesoscopic point of view, a new concept of soft matching is proposed innovatively. Then a soft Lasso’s approach to learn the soft dynamical equation for the physical mechanical relationship is proposed, too. Furthermore, a discrete iterative algorithm combining the Newton–Stokes term and the soft Lasso’s term is developed to simulate the motion of a ball falling in non-Newtonian fluids. The theory is validated by numerical examples and shows satisfactory results, which exhibit the chaotic phenomena, occasional sudden accelerations and continual random oscillations. These behaviors will maintain for a long time. Furthermore, the pattern of the motion is independent of the initial values as the solution to the Newton–Stokes equation. We find the soft relation in physics to characterize the chaotic phenomena based on the learning method, and improve the method of adding a simple random walk or normal distribution. Soft Lasso Non-Newtonian fluid Data-driven modeling Algebraic differential equation Yang, Ran verfasserin (orcid)0000-0001-6129-7547 aut Enthalten in No title available 131 (DE-627)352827580 1007-5704 nnns volume:131 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 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_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 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_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 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_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 131
allfields_unstemmed	10.1016/j.cnsns.2024.107829 doi (DE-627)ELV067147402 (ELSEVIER)S1007-5704(24)00015-7 DE-627 ger DE-627 rda eng Wu, Zongmin verfasserin aut A soft Lasso model for the motion of a ball falling in the non-Newtonian fluid 2024 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier From the mesoscopic point of view, a new concept of soft matching is proposed innovatively. Then a soft Lasso’s approach to learn the soft dynamical equation for the physical mechanical relationship is proposed, too. Furthermore, a discrete iterative algorithm combining the Newton–Stokes term and the soft Lasso’s term is developed to simulate the motion of a ball falling in non-Newtonian fluids. The theory is validated by numerical examples and shows satisfactory results, which exhibit the chaotic phenomena, occasional sudden accelerations and continual random oscillations. These behaviors will maintain for a long time. Furthermore, the pattern of the motion is independent of the initial values as the solution to the Newton–Stokes equation. We find the soft relation in physics to characterize the chaotic phenomena based on the learning method, and improve the method of adding a simple random walk or normal distribution. Soft Lasso Non-Newtonian fluid Data-driven modeling Algebraic differential equation Yang, Ran verfasserin (orcid)0000-0001-6129-7547 aut Enthalten in No title available 131 (DE-627)352827580 1007-5704 nnns volume:131 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 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_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 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_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 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_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 131
allfieldsGer	10.1016/j.cnsns.2024.107829 doi (DE-627)ELV067147402 (ELSEVIER)S1007-5704(24)00015-7 DE-627 ger DE-627 rda eng Wu, Zongmin verfasserin aut A soft Lasso model for the motion of a ball falling in the non-Newtonian fluid 2024 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier From the mesoscopic point of view, a new concept of soft matching is proposed innovatively. Then a soft Lasso’s approach to learn the soft dynamical equation for the physical mechanical relationship is proposed, too. Furthermore, a discrete iterative algorithm combining the Newton–Stokes term and the soft Lasso’s term is developed to simulate the motion of a ball falling in non-Newtonian fluids. The theory is validated by numerical examples and shows satisfactory results, which exhibit the chaotic phenomena, occasional sudden accelerations and continual random oscillations. These behaviors will maintain for a long time. Furthermore, the pattern of the motion is independent of the initial values as the solution to the Newton–Stokes equation. We find the soft relation in physics to characterize the chaotic phenomena based on the learning method, and improve the method of adding a simple random walk or normal distribution. Soft Lasso Non-Newtonian fluid Data-driven modeling Algebraic differential equation Yang, Ran verfasserin (orcid)0000-0001-6129-7547 aut Enthalten in No title available 131 (DE-627)352827580 1007-5704 nnns volume:131 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 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_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 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_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 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_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 131
allfieldsSound	10.1016/j.cnsns.2024.107829 doi (DE-627)ELV067147402 (ELSEVIER)S1007-5704(24)00015-7 DE-627 ger DE-627 rda eng Wu, Zongmin verfasserin aut A soft Lasso model for the motion of a ball falling in the non-Newtonian fluid 2024 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier From the mesoscopic point of view, a new concept of soft matching is proposed innovatively. Then a soft Lasso’s approach to learn the soft dynamical equation for the physical mechanical relationship is proposed, too. Furthermore, a discrete iterative algorithm combining the Newton–Stokes term and the soft Lasso’s term is developed to simulate the motion of a ball falling in non-Newtonian fluids. The theory is validated by numerical examples and shows satisfactory results, which exhibit the chaotic phenomena, occasional sudden accelerations and continual random oscillations. These behaviors will maintain for a long time. Furthermore, the pattern of the motion is independent of the initial values as the solution to the Newton–Stokes equation. We find the soft relation in physics to characterize the chaotic phenomena based on the learning method, and improve the method of adding a simple random walk or normal distribution. Soft Lasso Non-Newtonian fluid Data-driven modeling Algebraic differential equation Yang, Ran verfasserin (orcid)0000-0001-6129-7547 aut Enthalten in No title available 131 (DE-627)352827580 1007-5704 nnns volume:131 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 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_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 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_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 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_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 131
language	English
source	Enthalten in No title available 131 volume:131
sourceStr	Enthalten in No title available 131 volume:131
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container_title	No title available
authorswithroles_txt_mv	Wu, Zongmin @@aut@@ Yang, Ran @@aut@@
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author	Wu, Zongmin
spellingShingle	Wu, Zongmin misc Soft Lasso misc Non-Newtonian fluid misc Data-driven modeling misc Algebraic differential equation A soft Lasso model for the motion of a ball falling in the non-Newtonian fluid
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topic_title	A soft Lasso model for the motion of a ball falling in the non-Newtonian fluid Soft Lasso Non-Newtonian fluid Data-driven modeling Algebraic differential equation
topic	misc Soft Lasso misc Non-Newtonian fluid misc Data-driven modeling misc Algebraic differential equation
topic_unstemmed	misc Soft Lasso misc Non-Newtonian fluid misc Data-driven modeling misc Algebraic differential equation
topic_browse	misc Soft Lasso misc Non-Newtonian fluid misc Data-driven modeling misc Algebraic differential equation
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title	A soft Lasso model for the motion of a ball falling in the non-Newtonian fluid
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title_full	A soft Lasso model for the motion of a ball falling in the non-Newtonian fluid
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author-letter	Wu, Zongmin
doi_str_mv	10.1016/j.cnsns.2024.107829
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title_sort	a soft lasso model for the motion of a ball falling in the non-newtonian fluid
title_auth	A soft Lasso model for the motion of a ball falling in the non-Newtonian fluid
abstract	From the mesoscopic point of view, a new concept of soft matching is proposed innovatively. Then a soft Lasso’s approach to learn the soft dynamical equation for the physical mechanical relationship is proposed, too. Furthermore, a discrete iterative algorithm combining the Newton–Stokes term and the soft Lasso’s term is developed to simulate the motion of a ball falling in non-Newtonian fluids. The theory is validated by numerical examples and shows satisfactory results, which exhibit the chaotic phenomena, occasional sudden accelerations and continual random oscillations. These behaviors will maintain for a long time. Furthermore, the pattern of the motion is independent of the initial values as the solution to the Newton–Stokes equation. We find the soft relation in physics to characterize the chaotic phenomena based on the learning method, and improve the method of adding a simple random walk or normal distribution.
abstractGer	From the mesoscopic point of view, a new concept of soft matching is proposed innovatively. Then a soft Lasso’s approach to learn the soft dynamical equation for the physical mechanical relationship is proposed, too. Furthermore, a discrete iterative algorithm combining the Newton–Stokes term and the soft Lasso’s term is developed to simulate the motion of a ball falling in non-Newtonian fluids. The theory is validated by numerical examples and shows satisfactory results, which exhibit the chaotic phenomena, occasional sudden accelerations and continual random oscillations. These behaviors will maintain for a long time. Furthermore, the pattern of the motion is independent of the initial values as the solution to the Newton–Stokes equation. We find the soft relation in physics to characterize the chaotic phenomena based on the learning method, and improve the method of adding a simple random walk or normal distribution.
abstract_unstemmed	From the mesoscopic point of view, a new concept of soft matching is proposed innovatively. Then a soft Lasso’s approach to learn the soft dynamical equation for the physical mechanical relationship is proposed, too. Furthermore, a discrete iterative algorithm combining the Newton–Stokes term and the soft Lasso’s term is developed to simulate the motion of a ball falling in non-Newtonian fluids. The theory is validated by numerical examples and shows satisfactory results, which exhibit the chaotic phenomena, occasional sudden accelerations and continual random oscillations. These behaviors will maintain for a long time. Furthermore, the pattern of the motion is independent of the initial values as the solution to the Newton–Stokes equation. We find the soft relation in physics to characterize the chaotic phenomena based on the learning method, and improve the method of adding a simple random walk or normal distribution.
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title_short	A soft Lasso model for the motion of a ball falling in the non-Newtonian fluid
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doi_str	10.1016/j.cnsns.2024.107829
up_date	2024-07-06T20:15:49.460Z
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A soft Lasso model for the motion of a ball falling in the non-Newtonian fluid

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