• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.4 no.3 s.8
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• pp.9-22
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• 2005

Route travel cost in transportation networks consists of actual route travel cost and route perception cost. Since the route perception cost is differently perceived according to each origin and each destination, route search has limitation to reflect the note perception cost due to route enumeration problem. Thus, currently employed advanced traveller information systems (ATIS) have considered only actual route travel cost for providing route information. This study proposes an optimal and a K-route searching algorithm which are able to reflect the route perception cost but encompass route enumeration problem. For this purpose, this research defines the minimum nit of route as a link by adopting the link label technique in route searching, therefore the comparison of two adjacent links which can be finally expanded the comparison of two routes. In order to reflect the characteristics of route perception in real situation, an optimal shortest cost path algorithm that both the forward search from the origin and the backward search from the destination can be simultaneously processed is proposed. The proposed algorithm is applied for finding K number of shortest routes with an entire-path-deletion-type of K shortest route algorithm.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.44 no.1
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• pp.41-48
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• 2007

In this paper, we propose an optimal placement of sensor nodes with 2.4GHz wireless channel characteristics. The proposed method determines optimal transmission range based on log-normal path loss model, and optimal number of sensor nodes calculating the density of sensor nodes. For the lossless data transmission, we search the optimal locations with self-organizing feature maps(SOM) using transmission range, and number of sensor nodes. We demonstrate that optimal transmission range is 20m, and optimal number of sensor nodes is 8. We performed simulations on the searching for optimal locations and confirmed the link condition of sensor nodes.

• Journal of the Korea Society of Computer and Information
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• v.11 no.3
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• pp.117-124
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• 2006

In this paper, we propose the optimal migration path searching method including path adjustment and reassignment techniques for an efficient migration of mobile agent which has an autonomous ability for some task processing. In traditional agent system, if the various and large quantify of task processing were required from the users, it could be derive excessive network traffic and overload due to increasing the size of agent. And also, if an agent migrates from node to node according to routing schedules specified by the user at which the most of network traffic occurs, it could not actively cope with particular situations such as communication loss and node obstacles and required much cost for node traversal Therefore. this paper presents the migration method of agent which can try to adjust and reassign path to the destination automatically through the optimal path search using by network traffic perception in stead of the passive routing schedule by the user. An optimal migration path searching and adjustment methods ensure the migration reliability on distributed nodes and reduce the traversal task processing time of mobile agent by avoiding network traffic paths and node obstacles.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.6
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• pp.941-947
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• 2018

Station transfers for smart card based railway networks refer to transfer pedestrian movements that occur at the origin and destination nodes rather than at a middle station. To calculate the optimum path for the railway network, a penalty for transfer pedestrian movement must be included in addition to the cost of within-car transit time. However, the existing link label-based path searching method is constructed so that the station transfer penalty between two links is detected. As such, station transfer penalties that appear at the origin and destination stations are not adequately reflected, limiting the effectiveness of the model. A ghost node may be introduced to expand the network, to make up for the station transfer penalty, but has a pitfall in that the link label-based path algorithm will not hold up effectively. This research proposes an optimal path search algorithm to reflect station transfer penalties without resorting to enlargement of the existing network. To achieve this, a method for applying a directline transfer penalty by comparing Ticket Gate ID and the line of the link is proposed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.12
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• pp.5015-5022
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• 2010

Most of the existing pattern mining techniques are capable of searching patterns according to the continuous change of the spatial information of an object but there is no constraint on the spatial information that must be included in the extracted pattern. Thus, the existing techniques are not applicable to the optimal path search between specific nodes or path prediction considering the nodes that a moving object is required to round during a unit time. In this paper, the precision of the path search according to the spatial hierarchy is analyzed using the Spatial-Temporal Optimal Moving Pattern(with Frequency & Weight) (STOPM(FW)) algorithm which searches for the optimal moving path by considering the most frequent pattern and other weighted factors such as time and cost. The result of analysis shows that the database retrieval time is minimized through the reduction of retrieval range applying with the spatial constraints. Also, the optimal moving pattern is efficiently obtained by considering whether the moving pattern is included in each hierarchical spatial scope of the spatial hierarchy or not.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.4
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• pp.493-498
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• 2004

A novel approach for path planning of a polygonal robot is presented. Traditional path planners perform extensive geometric searching to find the optimal path or to prove that there is no solution. The computation required to prove that there is no solution is equivalent to exhaustive search of the motion space, which is typically very expensive. Humans seems to use a set of several different path planning strategies to analyse the situation of the obstacles in the environment, and quickly recognize whether the path-planning problem is easy to solve, hard to solve or has no solution. This human path-planning strategies have motivated the development of the presented algorithm that combines qualitative shape reasoning and exhaustive geometric searching to speed up the path planning process. It has three planning stages consisting of identification of no-solution cases based on an enclosure test, a qualitative reasoning stage, and finally a complete search algorithm in case the previous two stages cannot determine of the existence of a solution path.

• Journal of the Korea Society for Simulation
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• v.19 no.3
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• pp.27-35
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• 2010

War-games using C4I systems have been used to improve the command ability of commanders and the fighting power of combat forces. During a war-game simulation, a commander makes a plan for the movement of a combat force and issues orders to the combat force according to the plan. If it is possible to minimize damages from the artillery of enemy forces and take the advantage position where is effective for attack/defense, we can hold a dominant position of the battlefield. Therefore, this papers proposes a genetic algorithm-based optimal path searching method. The proposed method creates an optimal path of a combat force by taking into consideration dangerous conditions of the battlefield in which the combat force is. This paper also shows the process of creating an optimal path by using a discrete event specification modeling and simulation method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.2
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• pp.430-435
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• 2007

In this paper, we propose an intelligent deployment of sensor network for reliable communication. The proposed method determines optimal transmission range based on the wireless channel characteristics, and searches the optimal number of sensor nodes, and optimal locations with SOFM. We calculate PRR against a distance uses the log-normal path loss model, and decide the communication range of sensor node from PRR. In order to verify the effectiveness of the proposed method, we performed simulations on the searching for intelligent deployment and checking for link condition of sensor network.

• Proceedings of the KIEE Conference
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• 2003.07a
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• pp.381-383
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• 2003

The authors have developed a solution method based on the incremental algorithm. The optimal load balance between feeders is found through the incremental algorithm with allowing the loop configuration. Therefore loops can be configured in the resulting configuration, and then we must eliminate all loops to satisfy radiality of distribution system because the distribution system is operated under radial status. But the optimal load balance through incremental algorithm is deteriorated when the loops are eliminated. In this paper, authors propose a new method which is to improve the searching procedure of path in the incremental algorithm, that is, so as not to make loop in the path configuration.

• The Journal of Korea Robotics Society
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• v.18 no.1
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• pp.1-9
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• 2023

This paper presents an optimal path planning strategy for aerial searching and surveying of a user-designated area using multiple Unmanned Aerial Vehicles (UAVs). The method is designed to deal with a single unseparated polygonal area, regardless of polygonal convexity. By defining the search area into a set of grids, the algorithm enables UAVs to completely search without leaving unsearched space. The presented strategy consists of two main algorithmic steps: cellular decomposition and path planning stages. The cellular decomposition method divides the area to designate a conflict-free subsearch-space to an individual UAV, while accounting the assigned flight velocity, take-off and landing positions. Then, the path planning strategy forms paths based on every point located in end of each grid row. The first waypoint is chosen as the closest point from the vehicle-starting position, and it recursively updates the nearest endpoint set to generate the shortest path. The path planning policy produces four path candidates by alternating the starting point (left or right edge), and the travel direction (vertical or horizontal). The optimal-selection policy is enforced to maximize the search efficiency, which is time dependent; the policy imposes the total path-length and turning number criteria per candidate. The results demonstrate that the proposed cellular decomposition method improves the search-time efficiency. In addition, the candidate selection enhances the algorithmic efficacy toward further mission time-duration reduction. The method shows robustness against both convex and non-convex shaped search area.