• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1216-1218
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• 1996

Genetic algorithm(GA) is useful to find optimal solution without any special mathematical modeling. This study presents to search optimal path of Autonomous Mobile Robot(AMR) by using GA without encoding and decoding procedure. Therefore, this paper shows that the proposed algorithm using GA can reduce the computation time to search the optimal path.

• Journal of Families and Better Life
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• v.11 no.1
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• pp.12-21
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• 1993

This Study focused on consumer information search and consumer satisfaction according to product characteristics and sex. For these purpose a survey was conducted using questionaires on 225 males 299 females that lived in Seoul. Statistics used for data were Frequency. Prequency. Percentile Mean Multiple Regression Analysis and Path Analysis. The major findings were: 1) I male Group reference orientation were effect on convenience experience credience goods and information search were effect on experience credience goods. 2) In Femal Group her job and information search effect on convenience experience credience goods and involvement effect on credience goods only.

• Korean Journal of Human Ecology
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• v.7 no.1
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• pp.61-74
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• 1998

The purpose of this study is to investigate the information search, information use and search outcomes. 420 students in Chungnam and Taejon area were surveyed. Questionnaire survey method and multiple regression and path analysis were used. Some major conclusions were as follows: 1) The levels of the information search, information use and search outcomes were relatively low. 2) The volumes of information search and the contents of information were mainly affected by psycho-behavioral variables. 3) The level of information use was affected by the content of information, desire to seek information, involvement, and previous knowledge. 4) The search outcome was affected positively by the information use, involvement, volume of information search, desire to seek information, and perceived risk. 5) The volume of information search and the information use were the parameter of the search outcomes.

• Journal of Korean Society of Transportation
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• v.24 no.3 s.89
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• pp.177-187
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• 2006

It is known that over one million car navigation devices are being currently used in Korea. Most. if not all, route guidance systems, however, Provide only one "best" route to users, not providing any options for various types of users to select. The current practice dose not consider each individual's different preferences. These days, a vast amount of information became available due to the rapid development in information processing technology. Thus, users Prefer choices to be given and like to select the one that suits him/her the "best" among available information. To provide such options in this Paper, we developed an algorithm that provides alternative routes that may not the "least cost" ones, but ones that are close to the "least cost" routes for users to select. The algorithm developed and introduced in the paper utilizes a link-based search method, rather than the traditional node-based search method. The link-based algorithm can still utilize the existing transportation network without any modifications, and yet enables to provide flexible route guidance to meet the various needs of users by allowing transfer to other modes and/or restricting left turns. The algorithm developed has been applied to a toy network and demonstrated successful implementation of the multi-path search algorithm for multi-purpose activities.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.500-503
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• 2003

The navigation problem of robot is one of the main themes to deal with conficts or interferences between obstacles and the robot itself In this case, while the robot avoids obstacles on the space, the passage route should be determined efficiently. In order to solve problems above, we have come up with the distance field space medel (DFM) and then, under known environment, we have presented the distance field A algorithm for passage route path search. In this research, the method of performing the 3-dimensional passage route path search of robot under unknown environment is proposed. It is shown that the authors can build the distance search model the does not need space division by taking into account of sensor information to a distance field space model, and constructing this information as virtual obstacle information.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.3
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• pp.360-371
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• 1993

Flood search algorithm is known to be an effective routing mechanism for tactical application, since it provides high degree of survivability and robustness. But it is known that it has significant drawbacks with respect to the network efficiency [1]. We consider a tactical circuit-switched grid network with a maximum of four links and two priority classes of voice traffic, Using the minimum first-derivative length (MFDL) path, we improve the blocking probability performance of the circuit-switched network without increasing the call set-up time and processor loading of the algorithm.

• Smart Media Journal
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• v.9 no.4
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• pp.36-43
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• 2020

The Monte Carlo tree search (MCTS) is a popular method for implementing an intelligent game program. It has several hyper-parameters that require an optimization for showing the best performance. Due to the stochastic nature of the MCTS, the hyper-parameter optimization is difficult to solve. This paper uses the self-playing capability of the MCTS-based game program for optimizing the hyper-parameters. It seeks a winner path over the hyper-parameter space while performing the self-play. The top-q longest winners in the winner path compete for the final winner. The experiment using the 15-15-5 game (Omok in Korean name) showed a promising result.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.11a
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• pp.176-179
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• 2007

In this paper, we develop the path planning algorithm using the improved Dijkstra algorithm and the particle swarm optimization. To get the optimal path, at first we construct the MAKLINK on the world environment and then make a graph associated with the MAKLINK. From the graph, we obtain the Dijkstra path between the starting point and the destination point. From the optimal path, we search the improved Dijkstra path using the graph. Finally, applying the particle swarm optimization to the improved Dijkstra path, we obtain the optimal path for the mobile robot. It turns out that the proposed method has better performance than the result in [1].

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.184-186
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• 2006

We propose a new method for shortest path planning of mobile robots. The topological information of the graph is obtained by thinning method to generate the collision-free path of robot. And the travelling path is determined through hierarchical planning stages. The first stage generates an initial path by use of Dijkstra's algorithm. The second stage then generates the final path by use of dynamic programming (DP). The DP adjusts the intial path to reduce the total travelling distance of robot. Simulation results are presented to verify the performance of the proposed method.

• Journal of the Korea Society of Computer and Information
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• v.25 no.12
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• pp.135-144
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• 2020

In graph theory, the least-cost path is discovered by searching the shortest path between a start node and destination node. The least cost is calculated as a one-dimensional value that represents the difference in distance or price between two nodes, and the nodes and edges that comprise the lowest sum of costs between the linked nodes is the shortest path. However, it is difficult to determine the shortest path if each node has multiple attributes because the number of cost types that can appear is equal to the number of attributes. In this paper, a shortest path search scheme is proposed that considers multiple attributes using the Euclidean distance to satisfy various user requirements. In simulation, we discovered that the shortest path calculated using one-dimensional values differs from that calculated using the Euclidean distance for two-dimensional attributes. The user's preferences are reflected in multi attributes and it was different from one-dimensional attribute. Consequently, user requirements could be satisfied simultaneously by considering multiple attributes.