A Modeling Framework of Cyber-Physical-Social Systems with Human Behavior Classification Based on Machine Learning

Dongdong An; Jing Liu; Xiaohong Chen; Tengfei Li; Ling Yin

doi:10.1007/978-3-030-32409-4_37

A Modeling Framework of Cyber-Physical-Social Systems with Human Behavior Classification Based on Machine Learning

Dongdong An, Jing Liu, Xiaohong Chen, Tengfei Li, Ling Yin

Software Engineering Institute

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Scopus citations

Abstract

Cyber-Physical-Social Systems (CPSS) is an emerging complicated topic in recent years which focuses on the researches of a combination of cyberspace, physical space and social space. Different from traditional Cyber-Physical-Systems, CPSS contain human who interacts with the cyber and physical part more frequently. So how to capture and analyse human behaviors play a vital role in CPSS performance evaluation. To improve the analysis accuracy of CPSS, the paper proposes a new modelling framework – stohMCharts (stochastic hybrid MARTE statecharts) which is an extension of MARTE statecharts for stochastic hybrid system modelling and analysis. Compared to MARTE statechart, in stohMCharts, we can model the CPSS in a unified way. Also, we associate stohMCharts to NSHA (Networks Stochastic Hybrid Automata) and use statistical model checker UPPAAL-SMC to verify the stohMCharts. We apply an autonomous car as an example to explain the efficiency of our proposed approaches.

Original language	English
Title of host publication	Formal Methods and Software Engineering - 21st International Conference on Formal Engineering Methods, ICFEM 2019, Proceedings
Editors	Yamine Ait-Ameur, Shengchao Qin
Publisher	Springer
Pages	522-525
Number of pages	4
ISBN (Print)	9783030324087
DOIs	https://doi.org/10.1007/978-3-030-32409-4_37
State	Published - 2019
Event	21st International Conference on Formal Engineering Methods, ICFEM 2019 - Shenzhen, China Duration: 5 Nov 2019 → 9 Nov 2019

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	11852 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	21st International Conference on Formal Engineering Methods, ICFEM 2019
Country/Territory	China
City	Shenzhen
Period	5/11/19 → 9/11/19

Keywords

Cyber-Physical-Social Systems
Statistical model checking
Stochastic Hybrid Automata
Stochastic hybrid MARTE statecharts

Access to Document

10.1007/978-3-030-32409-4_37

Cite this

An, D., Liu, J., Chen, X., Li, T., & Yin, L. (2019). A Modeling Framework of Cyber-Physical-Social Systems with Human Behavior Classification Based on Machine Learning. In Y. Ait-Ameur, & S. Qin (Eds.), Formal Methods and Software Engineering - 21st International Conference on Formal Engineering Methods, ICFEM 2019, Proceedings (pp. 522-525). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11852 LNCS). Springer. https://doi.org/10.1007/978-3-030-32409-4_37

An, Dongdong ; Liu, Jing ; Chen, Xiaohong et al. / A Modeling Framework of Cyber-Physical-Social Systems with Human Behavior Classification Based on Machine Learning. Formal Methods and Software Engineering - 21st International Conference on Formal Engineering Methods, ICFEM 2019, Proceedings. editor / Yamine Ait-Ameur ; Shengchao Qin. Springer, 2019. pp. 522-525 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "A Modeling Framework of Cyber-Physical-Social Systems with Human Behavior Classification Based on Machine Learning",

abstract = "Cyber-Physical-Social Systems (CPSS) is an emerging complicated topic in recent years which focuses on the researches of a combination of cyberspace, physical space and social space. Different from traditional Cyber-Physical-Systems, CPSS contain human who interacts with the cyber and physical part more frequently. So how to capture and analyse human behaviors play a vital role in CPSS performance evaluation. To improve the analysis accuracy of CPSS, the paper proposes a new modelling framework – stohMCharts (stochastic hybrid MARTE statecharts) which is an extension of MARTE statecharts for stochastic hybrid system modelling and analysis. Compared to MARTE statechart, in stohMCharts, we can model the CPSS in a unified way. Also, we associate stohMCharts to NSHA (Networks Stochastic Hybrid Automata) and use statistical model checker UPPAAL-SMC to verify the stohMCharts. We apply an autonomous car as an example to explain the efficiency of our proposed approaches.",

keywords = "Cyber-Physical-Social Systems, Statistical model checking, Stochastic Hybrid Automata, Stochastic hybrid MARTE statecharts",

author = "Dongdong An and Jing Liu and Xiaohong Chen and Tengfei Li and Ling Yin",

note = "Publisher Copyright: {\textcopyright} 2019, Springer Nature Switzerland AG.; 21st International Conference on Formal Engineering Methods, ICFEM 2019 ; Conference date: 05-11-2019 Through 09-11-2019",

year = "2019",

doi = "10.1007/978-3-030-32409-4\_37",

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An, D, Liu, J, Chen, X, Li, T & Yin, L 2019, A Modeling Framework of Cyber-Physical-Social Systems with Human Behavior Classification Based on Machine Learning. in Y Ait-Ameur & S Qin (eds), Formal Methods and Software Engineering - 21st International Conference on Formal Engineering Methods, ICFEM 2019, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11852 LNCS, Springer, pp. 522-525, 21st International Conference on Formal Engineering Methods, ICFEM 2019, Shenzhen, China, 5/11/19. https://doi.org/10.1007/978-3-030-32409-4_37

A Modeling Framework of Cyber-Physical-Social Systems with Human Behavior Classification Based on Machine Learning. / An, Dongdong; Liu, Jing; Chen, Xiaohong et al.
Formal Methods and Software Engineering - 21st International Conference on Formal Engineering Methods, ICFEM 2019, Proceedings. ed. / Yamine Ait-Ameur; Shengchao Qin. Springer, 2019. p. 522-525 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11852 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - A Modeling Framework of Cyber-Physical-Social Systems with Human Behavior Classification Based on Machine Learning

AU - An, Dongdong

AU - Liu, Jing

AU - Chen, Xiaohong

AU - Li, Tengfei

AU - Yin, Ling

PY - 2019

Y1 - 2019

N2 - Cyber-Physical-Social Systems (CPSS) is an emerging complicated topic in recent years which focuses on the researches of a combination of cyberspace, physical space and social space. Different from traditional Cyber-Physical-Systems, CPSS contain human who interacts with the cyber and physical part more frequently. So how to capture and analyse human behaviors play a vital role in CPSS performance evaluation. To improve the analysis accuracy of CPSS, the paper proposes a new modelling framework – stohMCharts (stochastic hybrid MARTE statecharts) which is an extension of MARTE statecharts for stochastic hybrid system modelling and analysis. Compared to MARTE statechart, in stohMCharts, we can model the CPSS in a unified way. Also, we associate stohMCharts to NSHA (Networks Stochastic Hybrid Automata) and use statistical model checker UPPAAL-SMC to verify the stohMCharts. We apply an autonomous car as an example to explain the efficiency of our proposed approaches.

AB - Cyber-Physical-Social Systems (CPSS) is an emerging complicated topic in recent years which focuses on the researches of a combination of cyberspace, physical space and social space. Different from traditional Cyber-Physical-Systems, CPSS contain human who interacts with the cyber and physical part more frequently. So how to capture and analyse human behaviors play a vital role in CPSS performance evaluation. To improve the analysis accuracy of CPSS, the paper proposes a new modelling framework – stohMCharts (stochastic hybrid MARTE statecharts) which is an extension of MARTE statecharts for stochastic hybrid system modelling and analysis. Compared to MARTE statechart, in stohMCharts, we can model the CPSS in a unified way. Also, we associate stohMCharts to NSHA (Networks Stochastic Hybrid Automata) and use statistical model checker UPPAAL-SMC to verify the stohMCharts. We apply an autonomous car as an example to explain the efficiency of our proposed approaches.

KW - Cyber-Physical-Social Systems

KW - Statistical model checking

KW - Stochastic Hybrid Automata

KW - Stochastic hybrid MARTE statecharts

UR - https://www.scopus.com/pages/publications/85076147261

U2 - 10.1007/978-3-030-32409-4_37

DO - 10.1007/978-3-030-32409-4_37

M3 - 会议稿件

AN - SCOPUS:85076147261

SN - 9783030324087

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 522

EP - 525

BT - Formal Methods and Software Engineering - 21st International Conference on Formal Engineering Methods, ICFEM 2019, Proceedings

A2 - Ait-Ameur, Yamine

A2 - Qin, Shengchao

PB - Springer

T2 - 21st International Conference on Formal Engineering Methods, ICFEM 2019

Y2 - 5 November 2019 through 9 November 2019

ER -

An D, Liu J, Chen X, Li T, Yin L. A Modeling Framework of Cyber-Physical-Social Systems with Human Behavior Classification Based on Machine Learning. In Ait-Ameur Y, Qin S, editors, Formal Methods and Software Engineering - 21st International Conference on Formal Engineering Methods, ICFEM 2019, Proceedings. Springer. 2019. p. 522-525. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-32409-4_37

A Modeling Framework of Cyber-Physical-Social Systems with Human Behavior Classification Based on Machine Learning

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