A study of the support vector machines and possibility-satisfiability decision models based on the chaotic time series

Peng Wang; Hong Mi

doi:10.1109/CSSS.2011.5972063

A study of the support vector machines and possibility-satisfiability decision models based on the chaotic time series

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

Abstract

This paper employs the possibility-satisfiability method which has been widely recognized in the field of social-economic decision-making. In order to further improve the accuracy of decision-making, it also innovatively introduces the method of support vector machines based on the chaotic time series. This method is used to predict the high point and the low point of the index in the possibility-satisfiability algorithm. Then the paper uses this model with the optimal full coverage time decision of the new type of rural social endowment insurance system in 20 central and western provinces in China as a case study. Meanwhile, the empirical research is also conducted in this paper and the results show that this model has provided a good decision support.

Original language	English
Title of host publication	2011 International Conference on Computer Science and Service System, CSSS 2011 - Proceedings
Pages	133-136
Number of pages	4
DOIs	https://doi.org/10.1109/CSSS.2011.5972063
State	Published - 2011
Externally published	Yes
Event	2011 International Conference on Computer Science and Service System, CSSS 2011 - Nanjing, China Duration: 27 Jun 2011 → 29 Jun 2011

Publication series

Name	2011 International Conference on Computer Science and Service System, CSSS 2011 - Proceedings

Conference

Conference	2011 International Conference on Computer Science and Service System, CSSS 2011
Country/Territory	China
City	Nanjing
Period	27/06/11 → 29/06/11

Keywords

chaotic time series
possibility-satisfiability
support vector machines

Access to Document

10.1109/CSSS.2011.5972063

Cite this

Wang, P., & Mi, H. (2011). A study of the support vector machines and possibility-satisfiability decision models based on the chaotic time series. In 2011 International Conference on Computer Science and Service System, CSSS 2011 - Proceedings (pp. 133-136). Article 5972063 (2011 International Conference on Computer Science and Service System, CSSS 2011 - Proceedings). https://doi.org/10.1109/CSSS.2011.5972063

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title = "A study of the support vector machines and possibility-satisfiability decision models based on the chaotic time series",

abstract = "This paper employs the possibility-satisfiability method which has been widely recognized in the field of social-economic decision-making. In order to further improve the accuracy of decision-making, it also innovatively introduces the method of support vector machines based on the chaotic time series. This method is used to predict the high point and the low point of the index in the possibility-satisfiability algorithm. Then the paper uses this model with the optimal full coverage time decision of the new type of rural social endowment insurance system in 20 central and western provinces in China as a case study. Meanwhile, the empirical research is also conducted in this paper and the results show that this model has provided a good decision support.",

keywords = "chaotic time series, possibility-satisfiability, support vector machines",

author = "Peng Wang and Hong Mi",

year = "2011",

doi = "10.1109/CSSS.2011.5972063",

language = "English",

isbn = "9781424497638",

series = "2011 International Conference on Computer Science and Service System, CSSS 2011 - Proceedings",

pages = "133--136",

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note = "2011 International Conference on Computer Science and Service System, CSSS 2011 ; Conference date: 27-06-2011 Through 29-06-2011",

}

Wang, P & Mi, H 2011, A study of the support vector machines and possibility-satisfiability decision models based on the chaotic time series. in 2011 International Conference on Computer Science and Service System, CSSS 2011 - Proceedings., 5972063, 2011 International Conference on Computer Science and Service System, CSSS 2011 - Proceedings, pp. 133-136, 2011 International Conference on Computer Science and Service System, CSSS 2011, Nanjing, China, 27/06/11. https://doi.org/10.1109/CSSS.2011.5972063

A study of the support vector machines and possibility-satisfiability decision models based on the chaotic time series. / Wang, Peng; Mi, Hong.
2011 International Conference on Computer Science and Service System, CSSS 2011 - Proceedings. 2011. p. 133-136 5972063 (2011 International Conference on Computer Science and Service System, CSSS 2011 - Proceedings).

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

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AB - This paper employs the possibility-satisfiability method which has been widely recognized in the field of social-economic decision-making. In order to further improve the accuracy of decision-making, it also innovatively introduces the method of support vector machines based on the chaotic time series. This method is used to predict the high point and the low point of the index in the possibility-satisfiability algorithm. Then the paper uses this model with the optimal full coverage time decision of the new type of rural social endowment insurance system in 20 central and western provinces in China as a case study. Meanwhile, the empirical research is also conducted in this paper and the results show that this model has provided a good decision support.

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Wang P, Mi H. A study of the support vector machines and possibility-satisfiability decision models based on the chaotic time series. In 2011 International Conference on Computer Science and Service System, CSSS 2011 - Proceedings. 2011. p. 133-136. 5972063. (2011 International Conference on Computer Science and Service System, CSSS 2011 - Proceedings). doi: 10.1109/CSSS.2011.5972063

A study of the support vector machines and possibility-satisfiability decision models based on the chaotic time series

Abstract

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Keywords

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