Stochastic stability analysis of composite dynamic system for particle swarm optimization
• Four types of forces acting on particles are extracted from the inherent kinematic analogy of PSO’s nature. • The stochastic composite dynamic model for PSO is proposed. • The stochastic stability of PSO is analyzed via constructing the corresponding Lyapunov functions. • The different influences...
Ausführliche Beschreibung
Autor*in: |
Dong, Wen Yong [verfasserIn] |
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Format: |
E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2022 |
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Umfang: |
17 |
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Übergeordnetes Werk: |
Enthalten in: Mo1264 Clinical Characteristics of Inflammatory Bowel Disease May Influence the Cancer Risk When Using Immunomodulators: Incident Cases of Cancer in a Multicenter Case-Control Study - Petrruzziello, Carmelina ELSEVIER, 2013, an international journal, New York, NY |
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Übergeordnetes Werk: |
volume:592 ; year:2022 ; pages:227-243 ; extent:17 |
Links: |
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DOI / URN: |
10.1016/j.ins.2021.12.095 |
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ELV056977700 |
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520 | |a • Four types of forces acting on particles are extracted from the inherent kinematic analogy of PSO’s nature. • The stochastic composite dynamic model for PSO is proposed. • The stochastic stability of PSO is analyzed via constructing the corresponding Lyapunov functions. • The different influences from optimization functions to PSO’s stability are discussed. • The convergence time is defined to measure the computing efficiency of PSO. | ||
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10.1016/j.ins.2021.12.095 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001692.pica (DE-627)ELV056977700 (ELSEVIER)S0020-0255(21)01316-5 DE-627 ger DE-627 rakwb eng 610 VZ 570 VZ BIODIV DE-30 fid 35.70 bkl 42.12 bkl 42.15 bkl Dong, Wen Yong verfasserin aut Stochastic stability analysis of composite dynamic system for particle swarm optimization 2022 17 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier • Four types of forces acting on particles are extracted from the inherent kinematic analogy of PSO’s nature. • The stochastic composite dynamic model for PSO is proposed. • The stochastic stability of PSO is analyzed via constructing the corresponding Lyapunov functions. • The different influences from optimization functions to PSO’s stability are discussed. • The convergence time is defined to measure the computing efficiency of PSO. Stochastic stability analysis Elsevier Composite dynamic system Elsevier Particle swarm optimization Elsevier Lyapunov function Elsevier Zhang, Ran Ran oth Enthalten in Elsevier Science Inc Petrruzziello, Carmelina ELSEVIER Mo1264 Clinical Characteristics of Inflammatory Bowel Disease May Influence the Cancer Risk When Using Immunomodulators: Incident Cases of Cancer in a Multicenter Case-Control Study 2013 an international journal New York, NY (DE-627)ELV011843691 volume:592 year:2022 pages:227-243 extent:17 https://doi.org/10.1016/j.ins.2021.12.095 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA 35.70 Biochemie: Allgemeines VZ 42.12 Biophysik VZ 42.15 Zellbiologie VZ AR 592 2022 227-243 17 |
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10.1016/j.ins.2021.12.095 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001692.pica (DE-627)ELV056977700 (ELSEVIER)S0020-0255(21)01316-5 DE-627 ger DE-627 rakwb eng 610 VZ 570 VZ BIODIV DE-30 fid 35.70 bkl 42.12 bkl 42.15 bkl Dong, Wen Yong verfasserin aut Stochastic stability analysis of composite dynamic system for particle swarm optimization 2022 17 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier • Four types of forces acting on particles are extracted from the inherent kinematic analogy of PSO’s nature. • The stochastic composite dynamic model for PSO is proposed. • The stochastic stability of PSO is analyzed via constructing the corresponding Lyapunov functions. • The different influences from optimization functions to PSO’s stability are discussed. • The convergence time is defined to measure the computing efficiency of PSO. Stochastic stability analysis Elsevier Composite dynamic system Elsevier Particle swarm optimization Elsevier Lyapunov function Elsevier Zhang, Ran Ran oth Enthalten in Elsevier Science Inc Petrruzziello, Carmelina ELSEVIER Mo1264 Clinical Characteristics of Inflammatory Bowel Disease May Influence the Cancer Risk When Using Immunomodulators: Incident Cases of Cancer in a Multicenter Case-Control Study 2013 an international journal New York, NY (DE-627)ELV011843691 volume:592 year:2022 pages:227-243 extent:17 https://doi.org/10.1016/j.ins.2021.12.095 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA 35.70 Biochemie: Allgemeines VZ 42.12 Biophysik VZ 42.15 Zellbiologie VZ AR 592 2022 227-243 17 |
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10.1016/j.ins.2021.12.095 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001692.pica (DE-627)ELV056977700 (ELSEVIER)S0020-0255(21)01316-5 DE-627 ger DE-627 rakwb eng 610 VZ 570 VZ BIODIV DE-30 fid 35.70 bkl 42.12 bkl 42.15 bkl Dong, Wen Yong verfasserin aut Stochastic stability analysis of composite dynamic system for particle swarm optimization 2022 17 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier • Four types of forces acting on particles are extracted from the inherent kinematic analogy of PSO’s nature. • The stochastic composite dynamic model for PSO is proposed. • The stochastic stability of PSO is analyzed via constructing the corresponding Lyapunov functions. • The different influences from optimization functions to PSO’s stability are discussed. • The convergence time is defined to measure the computing efficiency of PSO. Stochastic stability analysis Elsevier Composite dynamic system Elsevier Particle swarm optimization Elsevier Lyapunov function Elsevier Zhang, Ran Ran oth Enthalten in Elsevier Science Inc Petrruzziello, Carmelina ELSEVIER Mo1264 Clinical Characteristics of Inflammatory Bowel Disease May Influence the Cancer Risk When Using Immunomodulators: Incident Cases of Cancer in a Multicenter Case-Control Study 2013 an international journal New York, NY (DE-627)ELV011843691 volume:592 year:2022 pages:227-243 extent:17 https://doi.org/10.1016/j.ins.2021.12.095 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA 35.70 Biochemie: Allgemeines VZ 42.12 Biophysik VZ 42.15 Zellbiologie VZ AR 592 2022 227-243 17 |
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10.1016/j.ins.2021.12.095 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001692.pica (DE-627)ELV056977700 (ELSEVIER)S0020-0255(21)01316-5 DE-627 ger DE-627 rakwb eng 610 VZ 570 VZ BIODIV DE-30 fid 35.70 bkl 42.12 bkl 42.15 bkl Dong, Wen Yong verfasserin aut Stochastic stability analysis of composite dynamic system for particle swarm optimization 2022 17 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier • Four types of forces acting on particles are extracted from the inherent kinematic analogy of PSO’s nature. • The stochastic composite dynamic model for PSO is proposed. • The stochastic stability of PSO is analyzed via constructing the corresponding Lyapunov functions. • The different influences from optimization functions to PSO’s stability are discussed. • The convergence time is defined to measure the computing efficiency of PSO. Stochastic stability analysis Elsevier Composite dynamic system Elsevier Particle swarm optimization Elsevier Lyapunov function Elsevier Zhang, Ran Ran oth Enthalten in Elsevier Science Inc Petrruzziello, Carmelina ELSEVIER Mo1264 Clinical Characteristics of Inflammatory Bowel Disease May Influence the Cancer Risk When Using Immunomodulators: Incident Cases of Cancer in a Multicenter Case-Control Study 2013 an international journal New York, NY (DE-627)ELV011843691 volume:592 year:2022 pages:227-243 extent:17 https://doi.org/10.1016/j.ins.2021.12.095 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA 35.70 Biochemie: Allgemeines VZ 42.12 Biophysik VZ 42.15 Zellbiologie VZ AR 592 2022 227-243 17 |
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• Four types of forces acting on particles are extracted from the inherent kinematic analogy of PSO’s nature. • The stochastic composite dynamic model for PSO is proposed. • The stochastic stability of PSO is analyzed via constructing the corresponding Lyapunov functions. • The different influences from optimization functions to PSO’s stability are discussed. • The convergence time is defined to measure the computing efficiency of PSO. |
abstractGer |
• Four types of forces acting on particles are extracted from the inherent kinematic analogy of PSO’s nature. • The stochastic composite dynamic model for PSO is proposed. • The stochastic stability of PSO is analyzed via constructing the corresponding Lyapunov functions. • The different influences from optimization functions to PSO’s stability are discussed. • The convergence time is defined to measure the computing efficiency of PSO. |
abstract_unstemmed |
• Four types of forces acting on particles are extracted from the inherent kinematic analogy of PSO’s nature. • The stochastic composite dynamic model for PSO is proposed. • The stochastic stability of PSO is analyzed via constructing the corresponding Lyapunov functions. • The different influences from optimization functions to PSO’s stability are discussed. • The convergence time is defined to measure the computing efficiency of PSO. |
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Stochastic stability analysis of composite dynamic system for particle swarm optimization |
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