• Title/Summary/Keyword: 확률적 효용 최대화

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Application of Random Regret Minimization Model in the Context of Intercity Travel Mode Choice (지역간 수단선택에 있어서 확률적 후회 최소화 모형의 적용 연구)

  • Jin, Woo-Jeong;Lee, Jang-Ho
    • Journal of the Korean Society for Railway
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    • v.19 no.1
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    • pp.87-96
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    • 2016
  • The multinomial logit model, based on random utility maximization (RUM) theory, has been the predominant model used in travel mode choice contexts. In this paper, the travel mode choice model based on random regret minimization (RRM) theory is proposed as an alternative to the RUM model, and the applicability of the RRM model is examined. The presented model is applied to the case of inter-city travel mode choice in Korea. The empirical results show that the RUM model and RRM model have parameters that are consistent with the intuition. The goodness of fit statistics in the RRM model improved compared with the results of the RUM model. Consequently, these results show the possibility of using the RRM model in the context of travel mode choice.

Timed Bargaining Based Routing Protocol for the Vehicular Ad-Hoc Network (차량 애드 혹 네트워크 환경에서 제한시간 협상 게임 기반의 확률적 라우팅 프로토콜 기법)

  • Jang, Hee Tae;Kim, Sung Wook
    • KIPS Transactions on Computer and Communication Systems
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    • v.5 no.3
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    • pp.47-54
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    • 2016
  • In this paper, we propose a new opportunistic routing scheme based on timed bargaining game. The proposed algorithm effectively formulates the opportunistic routing mechanism as an repeated bargaining model using timed learning method. Additionally, we formulate a new contention window adjusting scheme for reduce collision rate. Simulation results indicate that the proposed scheme has excellent performance than other existing schemes under widely diverse VANET environments.

Korea-specified Maximum Expected Utility Model for the Probability of Default (기대효용최대화를 통한 한국형 기업 신용평가 모형)

  • Park, You-Sung;Song, Ji-Hyun;Choi, Bo-Seung
    • The Korean Journal of Applied Statistics
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    • v.20 no.3
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    • pp.573-584
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    • 2007
  • A well estimated probability of default is most important for constructing a good credit scoring process. The maximum expected utility (MEU) model has been suggested as an alternative of the traditional logistic regression model. Because the MEU model has been constructed using financial data arising from North America and European countries, the MEU model may not be suitable to Korean private firms. Thus, we propose a Korea-specific MEU model by estimating the parameters involved in kernel functions. This Korea-specific MEU model is illustrated using 34,057 private firms to show the performance of the MEU model relative to the usual logistic regression model.