• Journal of the Korean Operations Research and Management Science Society
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• v.27 no.2
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• pp.33-49
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• 2002

CBM (Condition-Based Maintenance) has increasingly drawn attention in industry because of its many benefits. CBM Problem Is characterized as a state-dependent scheduling model that demands simultaneous maintenance actions, each for an attribute that influences on machine condition. This problem is very hard to solve within conventional Markov decision process framework. In this paper, we present an intelligent machine maintenance scheduler, for which a new incremental decision tree learning method as evolutionary system identification model and shortest path problem as schedule generation model are developed. Although our approach does not guarantee an optimal scheduling policy in mathematical viewpoint, we verified through simulation based experiment that the intelligent scheduler is capable of providing good scheduling policy that can be used in practice.

• Proceedings of the Korean Information Science Society Conference
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• 2006.10a
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• pp.39-42
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• 2006

뉴럴네트워크에서 학습은 에러를 줄이는 방법으로 구현 된다. 이 때 parameter 공간에서 Risk function은 multi-minima potential로 표현 될 수 있으며 우리의 목적은 global minimum weight 좌표를 얻는 것이다. 이전의 연구로는 Attouch et al.의 damped oscillator 방정식을 이용한 방법이 있고, Qian의 critically damped oscillator를 통한 steepest descent의 momentum과 learning parameter 유도가 있다. 우리는 이 두 연구를 참고로 manifold 상에서 최단 경로인 geodesic을 Newton 역학의 Lagrangian에 적용함으로써 adaptive steepest descent 학습법을 얻었다. 우리는 이 새로운 방법을 Rosenbrock 과 Griewank 포텐셜들에 적용하여 그 성능을 알아 본다.

• Journal of the Korean Society for Precision Engineering
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• v.26 no.2
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• pp.63-70
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• 2009

This paper proposes a novel path finding approach of a mobile robot using RF strength in sensor network. In the experiments based on the proposed method, a mobile robot attempts to find its location, heading direction and the shortest path in the indoor environment. The experimental system consisting of mesh network shares node data and send them to base station. The triangulation and the proposed Grid method calculate the location and heading angle of the robot. In addition, the robot finds the shortest path by using the base station attached on it to receive data of environment around each node. Kalman filter reduces the straight line error when the robot estimates the strength of received signal. The experimental results show the effectiveness of the proposed algorithm.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.5
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• pp.46-55
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• 2012

This study proposes an estimate method of willingness to pay(WTP) for real-time route guidance systems using contingent valuation method(CVM) under double bounded dichotomous choice question(DBDCQ) and analysis for impact factors of WTP estimation. This study assumed that provided real-time traffic information service is optimal route concepts dealing with traffic conditions on origin-destination. Analysis targets were classified into two groups as short distance path and middle distance path for estimating WTP for realtime route guidance system in a year using the survival analysis method and the regression model with personal information, actual condition and satisfaction of information usage and users' awareness and usage of facilities. As a result, mean WTP of realtime route guidance system is 4,034won/year in short distance path, and 4,884won/year in middle distance path. Therefore real-time route guidance system for longer distance path is recognized as more valuable than shorter distance path. Moreover, the necessity of information was required on a higher income group and higher WTP was estimated on owners of vehicle group and lower awareness of a route group.

• Journal of Intelligence and Information Systems
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• v.11 no.1
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• pp.153-167
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• 2005

In this paper, we consider the problem of exploring unknown environments with a mobile robot or an autonomous character agent. Traditionally, research efforts to address the space exploration problem havefocused on the graph-based space representations and the graph search algorithms. Recently EXPLORE, one of the most efficient search algorithms, has been discovered. It traverses at most min$min(mn, d^2+m)$ edges where d is the deficiency of a edges and n is the number of edges and n is the number of vertices. In this paper, we propose DFS-RTA* and DFS-PHA*, two real-time graph search algorithms for directing an autonomous agent to explore in an unknown space. These algorithms are all built upon the simple depth-first search (DFS) like EXPLORE. However, they adopt different real-time shortest path-finding methods for fast backtracking to the latest node, RTA* and PHA*, respectively. Through some experiments using Unreal Tournament, a 3D online game environment, and KGBot, an intelligent character agent, we analyze completeness and efficiency of two algorithms.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.2
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• pp.243-253
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• 2019

First steps of Planetary exploration are usually conducted with the use of autonomous rovers. These rovers are capable of finding its own path and perform experiments about the planet's surface. This paper makes a proposal for a multi-agent system which effectively take the advantage of a blackboard system for share knowledge and effort of each agent. Agents use Reactive Model with the combination of Belief Desire Intension (BDI) Model and also use a Path Finding Algorithm for calculate shortest distance and a path for travel on the planet's surface. This approach can perform a surface exploration on a given terrain within a short period of time. Information which are gathered on the blackboard are used to make an output with detailed surface soil variance results. The developed Multi-Agent system performed well with different terrain sizes.

• KIPS Transactions on Computer and Communication Systems
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• v.1 no.2
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• pp.79-86
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• 2012

An economic ship routing means to sail a ship with a goal of minimizing the fuel consumption by utilizing weather forecast information, and various such systems have been recently studied. For a successful economic ship routing system, an efficient algorithm is needed to search an optimal geographical path, and most of the previous systems were approaching to that problem through a minimal static-cost path search algorithm based on the Dijkstra algorithm. To apply that kind of search algorithm, the cost of every edge assigned with the estimated fuel consumption should be constant. However, that assumption is not practical at all considering that the actual fuel consumption is determined by the weather condition when the ship will pass the edge. To overcome such a limitation, we propose a new optimal ship routing system based on a minimal dynamic-cost path search algorithm by properly modifying the Dijkstra algorithm. In addition, we propose a method which efficiently reduces the search space by using the $A^*$ algorithm to decrease the running time. We compared our system with the shortest path-based sailing method over ten testing routes and observed that the former reduced the estimated fuel consumption than the latter by 2.36% on average and the maximum 4.82% with little difference of estimated time of arrival.

• Journal of the Korea Society for Simulation
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• v.17 no.2
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• pp.91-103
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• 2008

In order to simulate the behavior of automated manufacturing systems, the performance of material handling systems should be measured dynamically. Multi-Agent technology could be well adapted for the development of simulator for distributed and intelligent manufacture systems. A multi-agent system is composed of one coordination agent and multiple application agents. Issues in AGVS simulator can be classified by the set-up and operating problems. Decisions on the number of vehicles, bi- or uni-directional guide-path, etc. are fallen into the set-up problem category, while deadlock tree algorithm and conflict resolution are in operating problem. In this paper, a multi-agent based deadlock-free simulator for automated guided vehicle system(AGVS) are proposed through the use of multi-agent technologies and the development of deadlock-free algorithm. In this AGVS simulator proposed, well-known Floyd algorithm is used to create AGVS Guide path, through which AGVS move. Also, AGVs avoid vehicle conflict and deadlock using check path algorithm. And Moving vehicle agents are operated in real-time control by coordination agent. AGV position is dynamically calculated based on the concept of rolling time horizon. Simulator receives and presents operating information of vehicle in AGVS Gaunt chart. The performance of the proposed algorithm and developed simulator based on multi-agent are validated through set of experiments.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.101-114
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• 2023

In the wartime, aircraft carrying out a mission to strike the enemy deep in the depth are exposed to the risk of being shoot down. As a key combat force in mordern warfare, it takes a lot of time, effot and national budget to train military flight personnel who operate high-tech weapon systems. Therefore, this study studied the path problem of predicting the route of emergency escape from enemy territory to the target point to avoid obstacles, and through this, the possibility of safe recovery of emergency escape military flight personnel was increased. based problem, transforming the problem into a TSP, VRP, and Dijkstra algorithm, and approaching it with an optimization technique. However, if this problem is approached in a network problem, it is difficult to reflect the dynamic factors and uncertainties of the battlefield environment that military flight personnel in distress will face. So, MDP suitable for modeling dynamic environments was applied and studied. In addition, GIS was used to obtain topographic information data, and in the process of designing the reward structure of MDP, topographic information was reflected in more detail so that the model could be more realistic than previous studies. In this study, value iteration algorithms and deterministic methods were used to derive a path that allows the military flight personnel in distress to move to the shortest distance while making the most of the topographical advantages. In addition, it was intended to add the reality of the model by adding actual topographic information and obstacles that the military flight personnel in distress can meet in the process of escape and escape. Through this, it was possible to predict through which route the military flight personnel would escape and escape in the actual situation. The model presented in this study can be applied to various operational situations through redesign of the reward structure. In actual situations, decision support based on scientific techniques that reflect various factors in predicting the escape route of the military flight personnel in distress and conducting combat search and rescue operations will be possible.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.1B
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• pp.35-45
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• 2009

In this study, a laboratory experiment has been performed on a S-curved channel with two curved sections. In the experiments, effects of 3-D velocity structures on mixing characteristics of tracer material were investigated. As a result, it was clearly noticed that the primary flow travels taking the shortest course of the meandering channel and has a very ununiform distribution at the bends. The secondary cell which was developing at the first bend disappears at the crossover, and then, at the next bend, secondary cell is re-developing in the opposite direction. The experimental results show that mixing of tracer is significantly affected by the combined action of ununiform primary flow and secondary cell. The ununiform primary flow separates the tracer cloud in the longitudinal direction, and the secondary cell further separates the retarding tracer cloud mainly in the transverse direction. As a result, these complex flow structures cause separation and spreading of tracer cloud both in the longitudinal and in the transverse directions. The measured dimensionless transverse dispersion coefficients calculated using 2-D routing procedure ranges 0.012-0.875, and is generally proportional to width to depth ratio (W/h). The predicted values calculated by the theoretical equation overestimate slightly the measured transverse dispersion coefficients.