• Journal of the Korea Society of Computer and Information
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• v.20 no.1
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• pp.29-37
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• 2015

Nowadays, the user-centric application based web 2.0 has replaced the web 1.0. The users gain and provide information by interactive network applications. As a result, traditional approaches that only extract and analyze users' local document operating behavior and network browsing behavior to build the users' preference profile cannot fully reflect their interests. Therefore this paper proposed a preference analysis and indicating approach based on the users' communication information from MicroBlog, such as reading, forwarding and @ behavior, and using the improved PersonalRank method to analyze the importance of a user to other users in the network and based on the users' communication behavior to update the weight of the items in the user preference. Simulation result shows that our proposed method outperforms the ontology model, TREC model, and the category model in terms of 11SPR value.

• Journal of the Korean Society of Safety
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• v.28 no.3
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• pp.118-122
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• 2013

For safe evacuation in the fire disaster, the evacuees must find the exit and evacuate quickly. Especially, if the evacuees don't know the location of the exit, they have to depend on the evacuation guidance system. Because the more smoke spread, the less visibility is decreasing, it is difficult to find the way to the exit by the naked eye. For theses reasons, the evacuation guidance system is highly important. However, the evacuation guidance system without change of direction has the risk that introduce to the dangerous area. In the evacuation safety assessment scenario by the evacuation simulation has the same problem. Because the evacuee in the simulation evacuate by the shortest route to the exit, the simulation result is same like the evacuation without the evacuation guidance system. In this study, it was used with MAS (Multi Agent System)-based simulation program including the evacuation guidance system to implement the change of evacuation by fire. Using this method, confidence of evacuation safety assessment can be increase.

• Journal of the Korea Society for Simulation
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• v.23 no.4
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• pp.9-19
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• 2014

The automotive industry has made much efforts to deliver finished vehicles to customers with speed and reliability. Decreasing the time a vehicle stays within an assembly plant from production release to shipment contributes to reduce the total order lead-time and consequently, the total transportation cost as well. Conventional shipment planning algorithms are limited in accommodating the dynamics of assembly plant operations as to finished vehicle shipment. This paper presents a market-based multi-agent shipment planning algorithm to optimize the performance of vehicle shipment process, capturing the operationally disruptive events. Experimental results using simulation show that the algorithm improves vehicle shipment performance with respect to lead time, labor efficiency, finished product quality, and transportation efficiency.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.670-675
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• 1994

Yhis paper describes a fault diagnosis simulation of the Real-Time Multiple Fault Dignosis System (RTMFDS) for forcasting faults in a system and deciding current machine state from signal information. Comparing with other diagnosis system for single fault,the system developed deals with multiple fault diagnosis,comprising two main parts. One is a remotesignal generating and transimission terminal and the other is a host system for fault diagnosis. Signal generator generate the random fault signal and the image information, and send this information to host. Host consists of various modules and agents such as Signal Processing Module(SPM) for sinal preprocessing, Performence Monotoring Module(PMM) for subsystem performance monitoring, Trigger Module(TM) for multi-triggering subsystem fault diagnosis, Subsystem Fault Diagnosis Agent(SFDA) for receiving trigger signal, formulating subsystem fault D\ulcornerB and initiating diagnosis, Fault Diagnosis Module(FDM) for simulating component fault with Hierarchical Artificial Neural Network (HANN), numerical models and Hofield network,Result Agent(RA) for receiving simulation result and sending to Treatment solver and Graphic Agent(GA). Each agent represents a separate process in UNIX operating system, information exchange and cooperation between agents was doen by IPC(Inter Process Communication : message queue, semaphore, signal, pipe). Numerical models are used to deseribe structure, function and behavior of total system, subsystems and their components. Hierarchical data structure for diagnosing the fault system is implemented by HANN. Signal generation and transmittion was performed on PC. As a host, SUN workstation with X-Windows(Motif)is used for graphic representation.

• Journal of the Korea Institute of Military Science and Technology
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• v.23 no.4
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• pp.337-345
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• 2020

The Weapon-Target Assignment(WTA) problem can be formulated as an optimization problem that minimize the threat of targets. Existing methods consider the trade-off between optimality and execution time to meet the various mission objectives. We propose a multi-agent reinforcement learning algorithm for WTA based on mean field game to solve the problem in real-time with nearly optimal accuracy. Mean field game is a recent method introduced to relieve the curse of dimensionality in multi-agent learning algorithm. In addition, previous reinforcement learning models for WTA generally do not consider weapon interference, which may be critical in real world operations. Therefore, we modify the reward function to discourage the crossing of weapon trajectories. The feasibility of the proposed method was verified through simulation of a WTA problem with multiple targets in realtime and the proposed algorithm can assign the weapons to all targets without crossing trajectories of weapons.

• Journal of Power Electronics
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• v.15 no.2
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• pp.455-468
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• 2015

A microgrid (MG) with integrated renewable energy resources can benefit both utility companies and customers. As a result, they are attracting a great deal of attention. The control of a MG is very important for the stable operation of a MG. The droop-control method is popular since it avoids circulating currents among the converters without using any critical communication between them. Traditional droop control methods have the drawback of an inherent trade-off between power sharing and voltage and frequency regulation. An adaptive droop control method is proposed, which can operate in both the island mode and the grid-connected mode. It can also ensure smooth switching between these two modes. Furthermore, the voltage and frequency of a MG can be restored by using the proposed droop controller. Meanwhile, the active power can be dispatched appropriately in both operating modes based on the capacity or running cost of the Distributed Generators (DGs). The global information (such as the average voltage and output active power of the MG and so on) required by the proposed droop control method to restore the voltage and frequency deviations can be acquired distributedly based on the Multi Agent System (MAS). Simulation studies in PSCAD demonstrate the effectiveness of the proposed control method.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.5
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• pp.390-397
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• 2013

This paper presents a consensus algorithm for uMAS (uncertain Multi-Agent Systems). Unlike previous results in which only nominal models for agents are considered, it is assumed that the uncertain agent model belongs to a known polytope set. In the middle of deriving the proposed algorithm, a convex set is found which includes all uncertainties in the problem using convexity of the polytope set. This set plays an important role in designing the consensus algorithm for uMAS. Based on the set, a consensus condition for uMAS is proposed and the corresponding consensus design problem is solved using LMI (Linear Matrix Inequality). Simulation result shows that the proposed consensus algorithm successfully leads to consensus of the state of uMAS.

• Journal of Internet Computing and Services
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• v.10 no.1
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• pp.101-110
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• 2009

Multi-agent systems are mostly used to integrate the intelligent and distributed approaches to various systems for effective sharing of resources and dynamic system reconfigurations. Object replication is usually used to implement fault tolerance and solve the problem of unexpected failures to the system. This paper presents the intelligent multi-agent distributed platform based on the dynamic object group management and proposes an object search technique based on the proposed filtered k-means (Fk-means). We propose Fk-means for the search mechanism to find alternative objects in the event of object failures and transparently reconnect client to the object. The filtering range of Fk-means value is set only to include relevant objects within the group to perform the search method efficiently. The simulation result shows that the proposed mechanism provides fast and accurate search for the distributed object groups.

• Journal of the Korea Society for Simulation
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• v.29 no.1
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• pp.71-79
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• 2020

As the urbanization trend in modern society continues, the concentration of the population induces the urban problems in the residential area. One of the well-known issues among various urban problems is the garbage problem, which causes deterioration of the residential environment of citizens and directly affects the satisfaction of municipal administration. Such garbage problem cannot be accurately predicted by analyzing the amount of waste emitted from residential areas, but it is necessary to analyze the lifestyle and characteristics of residents living in residential areas. In this study, we propose an agent-based residential modeling and simulation environment using discrete event system formalism to analyze the garbage problem and satisfaction level according to the distribution of residents in the residential area. To model the behavior of the residents, we utilized the Atomic Model to capture the temporal behavior. Also, we used the Coupled Model to model the multi-family and the building to enhance the reusability of the simulation model. Also, this study carried out simulation modeling and simulation for a multi-family residential area. The simulation results of the multi-family housing area show that considering the characteristics of the residents gives better results compared to the simulation results without considering the characteristics.

• Journal of Korea Spatial Information System Society
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• v.12 no.1
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• pp.76-84
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• 2010

Many pedestrian simulation models for micro-scale spaces as building indoor areas have been proposed for the last decade and two models - social force model and floor field model - are getting attention. Among these, CA-based floor field model is viewed more favourable for computer simulations than computationally complex social force model. However, Kirchner's floor field model has limitations in capturing the differences in dynamic values of different agents and this study proposes an enhanced algorithm. This study improved the floor field model in order for an agent to be able to exclude the influences of its own dynamic values by changing the data structure, and, also modified the initial dynamic value problem in order to fit more realistic environment. In the simulations, real 3D building data stored in a spatial DBMS were used considering future integration with indoor localization sensors and real time applications.