• 한국정보교육학회:학술대회논문집
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• 2010.08a
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• pp.227-233
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• 2010

Graph is applied to GIS, Network, AI and so on. We use graph concept in our daily life unconsciously. So this paper describe how graph concept is used when robot searches shortest path between two distinct vertices. It is performed in real world. For this, it consists of three step; maze traverse, graph generation, and shortest path search. Maze traverse steps is that robot navigates maze. It is most difficult step. Graph generation step is to represent structural information into graph. Shortest path search step is to that robot move between two vertices. It is not implemented yet. So we introduce process in design level.

• Journal of The Korean Association of Information Education
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• v.20 no.3
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• pp.243-254
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• 2016

This study has produced a checker of the shortest path search problem with a total of 19 questions as a web-based computer evaluation based on the 'TRAFFIC' questions of PISA 2012. It is because the computer has been settled as an indispensable and significant instrument in the process of solving the problems of everyday life and as a media that is underlying in assessment. Therefore, information gifted students should be able to solve the problem using the computer and give clear enough commands to the computer so that it can perform the procedure. In addition, since it is the age that the computational thinking is affecting every sectors, it should give students new educational stimuli. The relationship between the rate of correct answers and the time took to solve the problem through the shortest route search process showed a significant correlation the variable that affected the problem solving as the difficulty of the question rises due to the increase of nodes and edges turned out to be the node than the edge. It was revealed that information gifted students went through algorithmic thinking in the process of solving the shortest route search problem. And It could be confirmed cognitive characteristics of the information gifted students such as 'ability streamlining' and 'information structure memory'.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.64 no.4
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• pp.315-320
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• 2015

Proposal algorithm in this paper introduced cells, units of router group, for distributed processing of previous genetic algorithm. This paper presented ways to reduce search delay time of overall network through cell-based genetic algorithm. As a result of performance analysis comparing with existing genetic algorithm through experiments, the proposal algorithm was verified superior in terms of costs and delay time. Furthermore, time for routing an alternative path was reduced in proposal algorithm, in case that a network was damaged in existing optimal path algorithm, Dijkstra algorithm, and the proposal algorithm was designed to route an alternative path faster than Dijkstra algorithm, as it has a 2nd shortest path in cells of the damaged network. The study showed that the proposal algorithm can support routing of alternative path, if Dijkstra algorithm is damaged in a network.

• Journal of Korean Society of Transportation
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• v.23 no.6 s.84
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• pp.91-102
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• 2005

When it comes to the process of information storage, people are likely to organize individual information into the forms of groups rather than independent attributes, and put them together in their brains. Likewise, in case of finding the shortest path, this study suggests that a Hierarchical Road Network(HRN) model should be selected to browse the most desirable route, since the HRN model takes the process mentioned above into account. Moreover, most of drivers make a decision to select a route from origin to destination by road hierarchy. It says that the drivers feel difference between the link travel tine which was measured by driving and the theoretical link travel time. There is a different solution which has predicted the link travel time to solve this problem. By using this solution, the link travel time is predicted based on link conditions from time to time. The predicated link travel time is used to search the shortest path. Stochastic Process model uses the historical patterns of travel time conditions on links. The HRN model has compared favorably with the conventional shortest path finding model in tern of calculated speeds. Even more, the result of the shortest path using the HRN model has more similar to the survey results which was conducted to the taxi drivers. Taxi drivers have a strong knowledge of road conditions on the road networks and they are more likely to select a shortest path according to the real common sense.

• Journal of Korea Multimedia Society
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• v.12 no.9
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• pp.1333-1341
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• 2009

Tactical path-finding in computer games is path-finding where a path is selected by considering not only basic elements such as the shortest distance or the minimum time spend but also tactical information of surroundings when deciding character's moving trajectory. One way to include tactical information in path-finding is to represent a heuristic function as a sum of tactical quality multiplied by a weighting factor which is.. determined based on the degree of its importance. The choice of weighting factors for tactics is very important because it controls search performance and the characteristic of paths found. In this paper. we propose a method for improving a heuristic function by adjusting weights based on the difference between paths on examples given by a level designer and paths found during the search process based on the CUITent weighting factors. The proposed method includes the search algorithm modified to detect search errors and learn heuristics and the perceptron-like weight updating formular. Through simulations it is demonstrated how different paths found by tactical path-finding are from those by traditional path-finding. We analyze the factors that affect the performance of learning and show the example applied to the real game environments.

• Journal of Korean Society of Transportation
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• v.19 no.6
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• pp.183-194
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• 2001

The centralized traffic information system is to gather and analyze real-time traffic information, to receive traffic information request from user, and to send user processed traffic information such as a path finding. Position information, result of destination search, and other information. In the centralized traffic information system, a server received path-finding requests from many clients and must process clients requests in time. The algorithm of multiple path-finding is needed for a server to process clients request, effectively in time. For this reason, this paper presents a heuristic algorithm that decreases time to compute path-finding requests. This heuristic algorithm uses results of the neighbor nodes shortest path-finding that are computed periodically. Path-finding results of this multiple path finding algorithm to use results of neighbor nodes shortest path-finding are the same as a real optimal path in many cases, and are a little different from results of a real optimal path in non-optimal path. This algorithm is efficiently applied to the general topology and the hierarchical topology such as traffic network. The computation time of a path-finding request that uses results of a neighbor nodes shortest path-finding is 50 times faster than other algorithms such as one-to-one label-setting and label-correcting algorithms. Especially in non-optimal path, the average error rate is under 0.1 percent.

• Journal of Korean Society of Transportation
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• v.23 no.8 s.86
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• pp.171-179
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• 2005

This paper presents the algorithm using fuzzy inference that preestimates each link speed changed by different kinds of road situations. The elements we are considered are time zone, rainfall probability information and lane control information. This paper is consists of three parts. First of all we set up the fuzzy variables, and preestimate link speed changed by various road situations. For this process, we build the membership functions for each fuzzy variable and establish the fuzzy inference relations to find how fuzzy variables influence on link speed. Second, using backtracking method, we search the shortest route influenced by link speed changed by fuzzy inference. Third, we apply this algorithm to hypothetical network and find the shortest path. As a result, it is shown that this algorithm choose appropriate roundabout path according to the changing road situations.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.632-635
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• 2015

Proposal algorithm in this thesis introduced cells, units of router group, for distributed processing of previous genetic algorithm. This thesis presented ways to reduce search delay time of overall network through cell-based genetic algorithm. As a result of performance analysis comparing with existing genetic algorithm through experiments, the proposal algorithm was found superior in terms of costs and delay time. Furthermore, time for routing an alternative path was reduced in proposal algorithm, in case that a network was damaged in existing optimal path algorithm, Dijkstra algorithm, and the proposal algorithm was designed to route an alternative path faster than Dijkstra algorithm, as it has a 2nd shortest path in cells of the damaged network. The study showed that the proposal algorithm can support routing of alternative path, if Dijkstra algorithm is damaged in a network.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.117-127
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• 2012

Due to the recent expansion of the Web 2.0 -based services, along with the widespread of smartphones, online social network services are being popularized among users. Online social network services are the online community services which enable users to communicate each other, share information and expand human relationships. In the social network services, each relation between users is represented by a graph consisting of nodes and links. As the users of online social network services are increasing rapidly, the SNS are actively utilized in enterprise marketing, analysis of social phenomenon and so on. Social Network Analysis (SNA) is the systematic way to analyze social relationships among the members of the social network using the network theory. In general social network theory consists of nodes and arcs, and it is often depicted in a social network diagram. In a social network diagram, nodes represent individual actors within the network and arcs represent relationships between the nodes. With SNA, we can measure relationships among the people such as degree of intimacy, intensity of connection and classification of the groups. Ever since Social Networking Services (SNS) have drawn increasing attention from millions of users, numerous researches have made to analyze their user relationships and messages. There are typical representative SNA methods: degree centrality, betweenness centrality and closeness centrality. In the degree of centrality analysis, the shortest path between nodes is not considered. However, it is used as a crucial factor in betweenness centrality, closeness centrality and other SNA methods. In previous researches in SNA, the computation time was not too expensive since the size of social network was small. Unfortunately, most SNA methods require significant time to process relevant data, and it makes difficult to apply the ever increasing SNS data in social network studies. For instance, if the number of nodes in online social network is n, the maximum number of link in social network is n(n-1)/2. It means that it is too expensive to analyze the social network, for example, if the number of nodes is 10,000 the number of links is 49,995,000. Therefore, we propose a heuristic-based method for finding the shortest path among users in the SNS user graph. Through the shortest path finding method, we will show how efficient our proposed approach may be by conducting betweenness centrality analysis and closeness centrality analysis, both of which are widely used in social network studies. Moreover, we devised an enhanced method with addition of best-first-search method and preprocessing step for the reduction of computation time and rapid search of the shortest paths in a huge size of online social network. Best-first-search method finds the shortest path heuristically, which generalizes human experiences. As large number of links is shared by only a few nodes in online social networks, most nods have relatively few connections. As a result, a node with multiple connections functions as a hub node. When searching for a particular node, looking for users with numerous links instead of searching all users indiscriminately has a better chance of finding the desired node more quickly. In this paper, we employ the degree of user node vn as heuristic evaluation function in a graph G = (N, E), where N is a set of vertices, and E is a set of links between two different nodes. As the heuristic evaluation function is used, the worst case could happen when the target node is situated in the bottom of skewed tree. In order to remove such a target node, the preprocessing step is conducted. Next, we find the shortest path between two nodes in social network efficiently and then analyze the social network. For the verification of the proposed method, we crawled 160,000 people from online and then constructed social network. Then we compared with previous methods, which are best-first-search and breath-first-search, in time for searching and analyzing. The suggested method takes 240 seconds to search nodes where breath-first-search based method takes 1,781 seconds (7.4 times faster). Moreover, for social network analysis, the suggested method is 6.8 times and 1.8 times faster than betweenness centrality analysis and closeness centrality analysis, respectively. The proposed method in this paper shows the possibility to analyze a large size of social network with the better performance in time. As a result, our method would improve the efficiency of social network analysis, making it particularly useful in studying social trends or phenomena.

• Journal of Korean Society of Transportation
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• v.22 no.6
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• pp.101-108
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• 2004

The new transit fare in the Seoul Metropolitan is basically determined based on the distance-based fare system (DBFS). The total fare in DBFS consists of three parts- (1) basic fare, (2) transfer fare, and (3) extra fare. The fixed amount of basic fare for each mode is charged when a passenger gets on a mode, and it proceeds until traveling within basic travel distance. The transfer fare may be added when a passenger switches from the present mode to another. The extra fare is imposed if the total travel distance exceeds the basic travel distance, and after that, the longer distance the more extra fare based on the extra-fare-charging rule. This study proposes an algorithm for finding minimum fare route in DBFS. This study first exploits the link-label-based searching method to enable shortest path algorithms to implement without network expansion at junction nodes in inter-modal transit networks. Moreover, the link-expansion technique is adopted in order for each mode's travel to be treated like duplicated links, which have the same start and end nodes, but different link features. In this study, therefore, some notations associated with modes can be saved, thus the existing link-based shortest path algorithm is applicable without any loss of generality. For fare calculation as next steps, a mathematical formula is proposed to embrace fare-charging process using search process of two adjacent links illustrated from the origin. A shortest path algorithm for finding a minimum fare route is derived by converting the formula as a recursive form. The implementation process of the algorithm is evaluated through a simple network test.