Business scenario evaluation using Monte Carlo simulation on qualitative and quantitative hybrid model

Negoro

Mitsukuni

et al. 2012

Elect Comm in Japan

Self Cite

We propose a method of finding business risk factors in a qualitative and quantitative hybrid time-series simulation. The effect ratios of qualitative arcs in the hybrid simulation vary the output values of the simulation, so we define the effect ratios causing risks as business risk factors. Finding business risk factors in the entire ranges of effect ratios is time-consuming. It is considered that the probability distributions of effect ratios at the present time step and those at the previous time step are similar, and thus that the probability distributions at the present time step can be estimated. Our method finds business risk factors effectively in only the estimated ranges. Experimental results show that the precision and recall rate are 86%, and that search time is decreased by at least 20%. © 2012 Wiley Periodicals, Inc. Electron Comm Jpn, 95(3): 55-65, 2012; Published online in Wiley Online Library (wileyonlinelibrary.com).

Section: Time-series Qualitative and Quantitative Hybrid Simulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A method of finding business risk factors using the characteristics of probability distributions of effect ratios on qualitative and quantitative hybrid simulation

Negoro

Mitsukuni

et al. 2012

Elect Comm in Japan

Self Cite

“…1, the number of managers in charge of quality, the price, and the number of customers have quantitative values and their ranges. Additionally, we have introduced landmarks that are values for dividing the range to simulate the hybrid model more precisely [2]. Qualitative nodeQualitative nodes cannot be expressed by quantitative values. In order to represent a state of a qualitative node, five kinds of state expressions (qualitative values) indicating a state of qualitative nodes are input by a user: Quantitative arcQuantitative arcs have equations consisting of variables given in source nodes. Qualitative arcQualitative causal relations cannot be expressed by equations.…”

Section: Qualitative and Quantitative Hybrid Model With Uncertain mentioning

confidence: 99%

“…For appropriate decision‐making of policies under uncertain environment, it is important to evaluate policies based on both quantitative information and qualitative information [1]. In order to evaluate policies, we proposed a simulation method of the hybrid model including quantitative and qualitative information, and applied to a field of business forecasting such as marketing [2].…”

Section: Introductionmentioning

confidence: 99%

An interpolation method of uncertain landmarks for improving accuracy of simulation on qualitative and quantitative hybrid model

IEEJ Transactions Elec Engng

Akiyoshi

2012

Self Cite

It became possible to simulate a qualitative and quantitative hybrid model by dividing ranges of the model's quantitative variables with ‘landmarks’ and by associating divided ranges and kinds of qualitative values with each other. When landmarks are uncertain, it is difficult to set appropriate landmarks to guarantee the accuracy of the simulation. In order to guarantee the accuracy of the simulation, the proposed method interpolates uncertain landmarks based on initial values and reliable landmarks of the hybrid model. First, candidate positions, where landmarks are interpolated, are decided by associating the range including an initial value and an initial qualitative value. Next, values of landmarks are estimated by applying monotone cubic spline interpolation to the reliable landmarks. Through the application of the proposed method to a hybrid model, the difference between the simulation result on the hybrid model and the result derived from the quantitative model is decreased by 0.17 compared to the method without the interpolation. © 2012 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

“…The qualitative and quantitative hybrid model has operational nodes where the decision maker can set values as policies. The simulation on the hybrid model, called “qualitative and quantitative hybrid simulation,” can automatically generate scenarios [2, 3. The hybrid simulation decides the time‐series of changes in factors by using values on operational nodes, quantitative relations, and qualitative relations.…”

Section: Introductionmentioning

confidence: 99%

High‐speed generation of goal‐oriented scenarios using bidirectional combination of effect propagation on a qualitative and quantitative hybrid model

Morita

Akiyoshi

2012

Elect Comm in Japan

Self Cite

This paper addresses the high‐speed generation of goal‐oriented scenarios on a qualitative and quantitative hybrid model. The goal‐oriented scenarios can be generated efficiently by a bidirectional combination of forward propagation and backward propagation, if differences between the values related to each scenario are small on a certain time step. Thus, the method combines the scenarios when each value can be regarded as the same from qualitative value viewpoints. Furthermore, the proposed method decides the number of both propagations to generate the required number of goal‐oriented scenarios while decreasing the number of time‐consuming backward propagations. Experimental results show that the computational time for generating the required number of goal‐oriented scenarios is decreased by 98% compared to solely forward propagation. © 2012 Wiley Periodicals, Inc. Electron Comm Jpn, 95(12): 10–20, 2012; Published online in Wiley Online Library (wileyonlinelibrary.com). DOI 10.1002/ecj.11443