• Journal of Platform Technology
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• v.11 no.6
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• pp.21-27
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• 2023

In this paper, we introduce a reinforcement learning-based algorithm for personalized tourist path recommendations. The algorithm employs a reinforcement learning agent to explore tourist regions and identify optimal paths that are expected to enhance tourism experiences. The concept of tourism experience is defined through points of interest (POI) located along tourist paths within the tourist area. These metrics are quantified through aggregated evaluation scores derived from reviews submitted by past visitors. In the experimental setup, the foundational learning model used to find tour paths is the Deep Q-Network (DQN). Despite the limited availability of historical tourist behavior data, the agent adeptly learns travel paths by incorporating preference scores of tourist POIs and spatial information of the travel area.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3D
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• pp.361-366
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• 2006

It is widely known that the dynamic optimal path algorithm, adopting real-time path finding, can be supporting an optimal route with which users are satisfied economically and accurately. However, this system has to search optimal routes frequently for updating them. The proposed concept of optimizing search area lets it reach heuristic optimal path rapidly and efficiently. Since optimal path should be increased in proportion to an distance between origin and destination, tremendous calculating time and highly efficient computers are required for searching long distance journey. In this paper, as a result of which the concepts of partial solution and representative path are suggested. It was possible to find an optimal route by decreasing a half area in comparison with the previous method. Furthermore, as the size of the searching area is uniform, comparatively low efficient computer is required for long distance trip.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2007.11a
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• pp.281-282
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• 2007

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2417-2419
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• 2001

A path planning is one of the main subjects in a mobile robot. It is divided into two parts. One is a global path planning and another is a local path planning. This paper, using the formal two methods, presents that the mobile robot moves to multi-targets with avoiding unknown obstacles. For the shortest time and the lowest cost, the mobile robot has to find a optimal path between targets. To find a optimal global path, we used GA(Genetic Algorithm) that has advantage of optimization. After finding the global path, the mobile robot has to move toward targets without a collision. FLC(Fuzzy Logic Controller) is used for local path planning. FLC decides where and how faster the mobile robot moves. The validity of the study that searches the shortest global path using GA in multi targets and moves to targets without a collision using FLC, is verified by simulations.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.3
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• pp.102-112
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• 2015

In this paper we propose an application that can help you to find a school near you easily using smart phone GPS capabilities and Google map mounted on Android system. We use a shortest path algorithm to search near destinations. You can take advantage of the developed application when finding public places or destinations. Schools have usually been used as places for disaster evacuation, entrance examination, and qualifying examination. Even though you are not the young who use the smart phone easily, anyone can find a destination school easily with the proposed application of this paper.

• Journal of Sensor Science and Technology
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• v.27 no.4
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• pp.209-215
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• 2018

Recent research in animal behavior has shown that gradient information plays an important role in finding food and home. It is also important in optimization of performance because it indicates how the inputs should be adjusted for maximization/minimization of a performance index. We introduce perturbation as an additional input to obtain gradient information. Unlike the typical approach of calculating the gradient from the derivative, the proposed processing is very robust to noise since it is performed as a summation. Experimental results prove the validity of the process of spatial gradient acquisition. Quantitative indices for measuring the effect of the amplitude and the frequency are developed based on linear regression analysis. Drones are very useful for environmental monitoring and an autonomous path planning is required for unstructured environment. Guiding the drone for finding the origin of the interested physical property is done by estimating the gradient of the sensed value and generating the drone trajectories in the direction which maximizes the sensed value. Simulation results show that the proposed method can be successfully applied to identify the source of the physical quantity of interest by utilizing it for path planning of an autonomous drone in 3D environment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.7
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• pp.1442-1448
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• 2003

Network Management become more and more important issue in the network environment in which many applications such as Mail, teleconferencing, WWW and database software are operated. It can be possible for The Bridge and Router forwarding data to select next hop device which results in routing incorrect path from the viewpoint of network design. In this paper we address the problem of finding the detour routing path due to incorrect setting on routing devices. We propose the new algorithm for finding detour muting path based on hierarchical network structure analysis using information from SNMP MIB. To prove the correctness of the unposed algorithm we have done simulation with predefined data. Simulation results show that the algorithm finds detour path correctly.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.08a
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• pp.87-90
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• 2008

Dynamic Heuristic(DH) is not fixed data and is dynamically modified using transferred real time road data from server In this paper, we propose path-finding algorithm with Maximum Speed Dynamic Heuristic (DH-MAX) and do an experiment. The DH-MAX is to be used the highest speed as DH, in real map divided by same sire. And proposed algorithm searches path using the priority searching only of the fixed data, but also the highest speed with real time information. In the performance test, the quality of path is enhanced but the cost of searching is increased than $A^*$ algorithm.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.763-767
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• 1994

The measured vibration on a machine or a structure is shaped by the excitation waveform and the path transfer function. Mechanism diagnostics tends to focus on retrieving source featurce by minimzing the effects of the structural path, while in structural diagnostics we are more interested in minimizing source effects and retrieving path parameters. In structural diagnostics, therefore, there are experimental issues of gathering data that are independent source effects and finding a transfer function signature that reveals structural defects. This paper describes how the transfer function can be obtained more accurately by experiment using the compatibility relationship which is newly discovered.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2010.04a
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• pp.27-28
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• 2010

Finding shortest path technique running time differs depending on applying of the algorithm and data, and also used a lot of difference in effectiveness depending on the environment occurs. Therefore, the algorithm and environment based on this study, the relationship between optimal solutions and compare running time.