Application of trembling-hand perfect equilibrium to Nash nonlinear Grey Bernoulli model: an example of BRIC's GDP forecasting.

Saved in:
Bibliographic Details
Title: Application of trembling-hand perfect equilibrium to Nash nonlinear Grey Bernoulli model: an example of BRIC's GDP forecasting.
Authors: Hsin, Pei-Han1, Chen, Chun-I2 eddychen777@gmail.com
Source: Neural Computing & Applications. Dec2017 Supplement 1, Vol. 28, p269-274. 6p.
Subjects: Gray forecasting model, Gross domestic product, Nash equilibrium, Bernoulli hypothesis (Risk), Linear property
Abstract: The traditional Grey forecasting model, GM(1,1), is characterized by its linear property. The Nash nonlinear Grey Bernoulli model further increases the forecasting accuracy by considering two governing parameters in the model. Because of the multiple Nash solutions, this study uses trembling-hand perfect equilibrium to refine the NNGBM and then obtains higher forecasting accuracy. This study mathematically proves that the proposed model is feasible and efficient. Finally, NNGBM with trembling-hand perfect equilibrium is used to forecast GDP of four fast-growing countries, Brazil, Russia, India and China, which are abbreviated as BRIC. The results show that BRIC's GDP is keeping on growing. [ABSTRACT FROM AUTHOR]
Copyright of Neural Computing & Applications is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
FullText Links:
  – Type: pdflink
Text:
  Availability: 0
Header DbId: egs
DbLabel: Engineering Source
An: 126403758
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Application of trembling-hand perfect equilibrium to Nash nonlinear Grey Bernoulli model: an example of BRIC's GDP forecasting.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Hsin%2C+Pei-Han%22">Hsin, Pei-Han</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Chen%2C+Chun-I%22">Chen, Chun-I</searchLink><relatesTo>2</relatesTo><i> eddychen777@gmail.com</i>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Neural+Computing+%26+Applications%22">Neural Computing & Applications</searchLink>. Dec2017 Supplement 1, Vol. 28, p269-274. 6p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Gray+forecasting+model%22">Gray forecasting model</searchLink><br /><searchLink fieldCode="DE" term="%22Gross+domestic+product%22">Gross domestic product</searchLink><br /><searchLink fieldCode="DE" term="%22Nash+equilibrium%22">Nash equilibrium</searchLink><br /><searchLink fieldCode="DE" term="%22Bernoulli+hypothesis+%28Risk%29%22">Bernoulli hypothesis (Risk)</searchLink><br /><searchLink fieldCode="DE" term="%22Linear+property%22">Linear property</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: The traditional Grey forecasting model, GM(1,1), is characterized by its linear property. The Nash nonlinear Grey Bernoulli model further increases the forecasting accuracy by considering two governing parameters in the model. Because of the multiple Nash solutions, this study uses trembling-hand perfect equilibrium to refine the NNGBM and then obtains higher forecasting accuracy. This study mathematically proves that the proposed model is feasible and efficient. Finally, NNGBM with trembling-hand perfect equilibrium is used to forecast GDP of four fast-growing countries, Brazil, Russia, India and China, which are abbreviated as BRIC. The results show that BRIC's GDP is keeping on growing. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Neural Computing & Applications is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=126403758
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1007/s00521-016-2340-6
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 6
        StartPage: 269
    Subjects:
      – SubjectFull: Gray forecasting model
        Type: general
      – SubjectFull: Gross domestic product
        Type: general
      – SubjectFull: Nash equilibrium
        Type: general
      – SubjectFull: Bernoulli hypothesis (Risk)
        Type: general
      – SubjectFull: Linear property
        Type: general
    Titles:
      – TitleFull: Application of trembling-hand perfect equilibrium to Nash nonlinear Grey Bernoulli model: an example of BRIC's GDP forecasting.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Hsin, Pei-Han
      – PersonEntity:
          Name:
            NameFull: Chen, Chun-I
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 02
              M: 12
              Text: Dec2017 Supplement 1
              Type: published
              Y: 2017
          Identifiers:
            – Type: issn-print
              Value: 09410643
          Numbering:
            – Type: volume
              Value: 28
          Titles:
            – TitleFull: Neural Computing & Applications
              Type: main
ResultId 1