Hybrid simulation on qualitative and quantitative integrated model using Monte Carlo method

Masaki Samejima; Keisuke Negoro; Masanori Akiyoshi; Norihisa Komoda; Koshichiro Mitsukuni

Hybrid simulation on qualitative and quantitative integrated model using Monte Carlo method

Masaki Samejima, Keisuke Negoro, Masanori Akiyoshi, Norihisa Komoda, Koshichiro Mitsukuni

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

Abstract

We propose a simulation method on qualitative and quantitative hybrid model. In order to evaluate factors of a model with qualitative causal relations, we introduce a statistical approach based on propagation and combination of effects of factors by Monte Carlo simulation. In propagating an effect, we divide a range of a quantitative factor by landmarks and decide an effect to a destination node based on the divided ranges. In combining effects, we deicide an effect of each causal relation using effects ratio and sum all effects. Through applied results to practical models, it is confirmed that there are mostly same between results derived from quantitative relations and results derived from the proposed method at 0.05 alpha-level.

Original language	English
Title of host publication	Summer Computer Simulation Conference 2007, SCSC'07, Part of the 2007 Summer Simulation Multiconference, SummerSim'07
Pages	1315-1320
Number of pages	6
Volume	2
Publication status	Published - 2007
Externally published	Yes
Event	Summer Computer Simulation Conference 2007, SCSC 2007, Part of the 2007 Summer Simulation Multiconference, SummerSim 2007 - San Diego, CA Duration: 2007 Jul 15 → 2007 Jul 18

Other

Other	Summer Computer Simulation Conference 2007, SCSC 2007, Part of the 2007 Summer Simulation Multiconference, SummerSim 2007
City	San Diego, CA
Period	07/7/15 → 07/7/18

Keywords

Monte Carlo simulation
Qualitative and quantitative hybrid model

ASJC Scopus subject areas

Modelling and Simulation

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Hybrid simulation on qualitative and quantitative integrated model using Monte Carlo method. / Samejima, Masaki; Negoro, Keisuke; Akiyoshi, Masanori; Komoda, Norihisa; Mitsukuni, Koshichiro.

Summer Computer Simulation Conference 2007, SCSC'07, Part of the 2007 Summer Simulation Multiconference, SummerSim'07. Vol. 2 2007. p. 1315-1320.

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

Samejima, M, Negoro, K, Akiyoshi, M, Komoda, N & Mitsukuni, K 2007, Hybrid simulation on qualitative and quantitative integrated model using Monte Carlo method. in Summer Computer Simulation Conference 2007, SCSC'07, Part of the 2007 Summer Simulation Multiconference, SummerSim'07. vol. 2, pp. 1315-1320, Summer Computer Simulation Conference 2007, SCSC 2007, Part of the 2007 Summer Simulation Multiconference, SummerSim 2007, San Diego, CA, 07/7/15.

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N2 - We propose a simulation method on qualitative and quantitative hybrid model. In order to evaluate factors of a model with qualitative causal relations, we introduce a statistical approach based on propagation and combination of effects of factors by Monte Carlo simulation. In propagating an effect, we divide a range of a quantitative factor by landmarks and decide an effect to a destination node based on the divided ranges. In combining effects, we deicide an effect of each causal relation using effects ratio and sum all effects. Through applied results to practical models, it is confirmed that there are mostly same between results derived from quantitative relations and results derived from the proposed method at 0.05 alpha-level.

AB - We propose a simulation method on qualitative and quantitative hybrid model. In order to evaluate factors of a model with qualitative causal relations, we introduce a statistical approach based on propagation and combination of effects of factors by Monte Carlo simulation. In propagating an effect, we divide a range of a quantitative factor by landmarks and decide an effect to a destination node based on the divided ranges. In combining effects, we deicide an effect of each causal relation using effects ratio and sum all effects. Through applied results to practical models, it is confirmed that there are mostly same between results derived from quantitative relations and results derived from the proposed method at 0.05 alpha-level.

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