• International Journal of Highway Engineering
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• v.14 no.4
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• pp.163-173
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• 2012

PURPOSES : The purpose of this study is to check the possibilities of traffic pattern analysis using MatSIM for urban road network operation in incident case. METHODS : One of the stochastic dynamic models is MatSIM. MatSIM is a transportation simulation tool based on stochastic dynamic model and activity based model. It is an open source software developed by IVT, ETH zurich, Switzerland. In MatSIM, various scenario comparison analyses are possible and analyses results are expressed using the visualizer which shows individual vehicle movements and traffic patterns. In this study, trip distribution in 24-hour, traffic volume, and travel speed using MatSIM are similar to those of measured values. Therefore, results of MatSIM are reasonable comparing with measured values. Traffic patterns are changed according to incident from change of individual behavior. RESULTS : The simulation results and the actual measured values are similar. The simulation results show reasonable ranges which can be used for traffic pattern analysis. CONCLUSIONS : The change of traffic pattern including trip distribution, traffic volumes and speeds according to various incident scenarios can be used for traffic control policy decision to provide effective operation of urban road network.

• Journal of Korean Institute of Industrial Engineers
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• v.32 no.1
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• pp.61-73
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• 2006

This paper deals with traveling salesman problem(TSP) with the stochastic travel time. Practically, the travel time between demand points changes according to day and time zone because of traffic interference and jam. Since the almost pervious studies focus on TSP with the deterministic travel time, it is difficult to apply those results to logistics problem directly. But many logistics problems are strongly related with stochastic situation such as stochastic travel time. We need to develop the efficient solution method for the TSP with stochastic travel time. From the previous researches, we know that Q-learning technique gives us to deal with stochastic environment and neural network also enables us to calculate the Q-value of Q-learning algorithm. In this paper, we suggest an algorithm for TSP with the stochastic travel time integrating Q-learning and neural network. And we evaluate the validity of the algorithm through computational experiments. From the simulation results, we conclude that a new route obtained from the suggested algorithm gives relatively more reliable travel time in the logistics situation with stochastic travel time.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1173-1176
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• 1996

Multilayer feedforward networks may be applied to identify the deterministic relationship between input and output data. When the results from the network require a high level of assurance, considering of the stochastic relationship between the data may be very important. The variance is one of the useful parameters to represent the stochastic relationship. This paper presents a new algorithm for a multilayer feedforward network to learn the variance of dispersed data without preliminary calculation of variance. In this paper, the network with this learning algorithm is named as a variance learning neural network(VALEAN). Computer simulation examples are utilized for the demonstration and the evaluation of VALEAN.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.6
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• pp.121-127
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• 1997

Multilayer feedforward networks may be applied to identify the deterministic relationship between input and output data. When the results from the network require a high level of assurance, consideration of the stochastic relationship between the input and output data may be very important. Variance is one of the effective parameters to deal with the stochastic relationship. This paper presents a new algroithm for a multilayer feedforward network to learn the variance of dispersed data without preliminary calculation of variance. In this paper, the network with this learning algorithm is named as a variance learning neural network(VALEAN). Computer simulation examples are utilized for the demonstration and the evaluation of VALEAN.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.3C
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• pp.141-146
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• 2005

The authors investigate the convergence speed problem of nonlinear adaptive equalization. Convergence constraints and time constant of radial basis function network using stochastic gradient (RBF-SG) algorithm is analyzed and a method of making time constant independent of hidden-node output power by using sample-by-sample node output power estimation is derived. The method for estimating the node power is to use a single-pole low-pass filter. It is shown by simulation that the proposed algorithm gives faster convergence and lower minimum MSE than the RBF-SG algorithm.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.3
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• pp.49-57
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• 2018

In a previous article, for analyzing a stochastic activity network, Cho proposed a method for estimating the moments (mean, variance, skewness, kurtosis) of the project completion time under the assumption that the durations of activities are independently and normally distributed. Developed in the present article is a method for estimating those moments for stochastic activity networks which allow any type of distributions for activity durations. The proposed method uses the moment matching approach to discretize the distribution function of activity duration, and then a discrete inverse-transform method to determine activity durations to be used for calculating the project completion time. The proposed method can be easily applied to large-sized activity networks, and computationally more efficient than Monte Carlo simulation, and its accuracy is comparable to that of Monte Carlo simulation.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.395-398
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• 2011

This paper introduces stochastic cash-flow modeling integrated with simulation based scheduling. The system makes use of CPM schedule data exported from commercial scheduling software, computes the best fit probability distribution functions (PDFs) of historical activity durations, assigns the PDFs identified to respective activities, simulates the schedule network, computes the deterministic and stochastic project cash-flows, plots the corresponding cash flow diagrams, and estimates the best fit PDFs of overdraft and net profit of a project. It analyzes the effect of different distributions of activity durations on the distribution of overdrafts and net profits, and improves reliability compared to deterministic cash flow analysis.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.393-399
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• 2009

This paper introduces an automated tool named Advanced Stochastic Schedule Simulation System (AS4). The system automatically integrates CPM schedule data exported from Primavera Project Planner (P3) and historical activity duration data obtained from a project data warehouse, computes the best fit probability distribution functions (PDFs) of historical activity durations, assigns the PDFs identified to respective activities, computes the optimum number of simulation runs, simulates the schedule network for the optimum number of simulation runs, and estimates the best fit PDF of project completion times (PCTs). AS4 improves the reliability of simulation-based scheduling by effectively dealing with the uncertainties of the activities' durations, increases the usability of the schedule data obtained from commercial CPM software, and effectively handles the variability of the PCTs by finding the best fit PDF of PCTs. It is designed as an easy-to-use computer tool programmed in MATLAB. AS4 encourages the use of simulation-based scheduling because it is simple to use, it simplifies the tedious and burdensome process involved in finding the PDFs of the many activities' durations and in assigning the PDFs to the many activities of a new network under modeling, and it does away with the normality assumptions used by most simulation-based scheduling systems in modeling PCTs.

• Journal of the Korea Society for Simulation
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• v.10 no.2
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• pp.61-74
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• 2001

The reliability evaluation of the large scale network becomes very complicate according to the growing size of network. Moreover if the reliability is not constant but follows probability distribution function, it is almost impossible to compute them in theory. This paper studies the network evaluation methods in order to overcome such difficulties. For this an efficient path set algorithm which seeks the path set connecting the start and terminal nodes efficiently is developed. Also, various variance reduction techniques are applied to compute the system reliability to enhance the simulation performance. As a numerical example, a large scale network is given. The comparisons of the path set algorithm and the variance reduction techniques are discussed.

• The KIPS Transactions:PartA
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• v.8A no.3
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• pp.217-226
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• 2001

In this paper, for continuous media access operations performed by Clustered Continuous Media Storage Server (CCMSS) system, we present the analytical model based on the open queueing network, which considers simultaneously two critical delay factors, the disk I/O and the internal network, in the CCMSS system. And we derive by using the analytical model the stochastic model for the total service delay time in the system. Next, we propose the integrated stochastic admission control model for the CCMSS system, which estimate the maximum number of admittable service requests at the allowable service failure rate by using the derived stochastic model and apply the derived number of requests in the admission control operation. For the performance evaluation of the proposed model, we evaluated the deadline miss rates by means of the previous stochastic model considering only the disk I/O and the propose stochastic model considering the disk I/O and the internal network, and compared the values with the results obtained from the simulation under the real cluster-based distributed media server environment. The evaluation showed that the proposed admission control policy reflects more precisely the delay factors in the CCMSS system.