• Proceedings of the Korea Information Processing Society Conference
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• 2007.05a
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• pp.443-446
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• 2007

A new association rule mining algorithm, which reflects the strategic importance of associative relationships between items, was developed and presented in this paper. This algorithm exploits the basic framework of Apriori procedures and TSAA(transitive support association Apriori) procedure developed by Hyun and Choi in evaluating non-frequent itemsets. The algorithm considers the strategic importance(weight) of feature variables in the association rule mining process. Sample feature variables of strategic importance include: profitability, marketing value, customer satisfaction, and frequency. A database with 730 transaction data set of a large scale discount store was used to compare and verify the performance of the presented algorithm against the existing Apriori and TSAA algorithms. The result clearly indicated that the new algorithm produced substantially different association itemsets according to the weights assigned to the strategic feature variables.

• IE interfaces
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• v.16 no.2
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• pp.117-124
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• 2003

This study focuses on the detailed explanation of the strategic allocation algorithm which can be used as an ATP(Available To Promise) from the perspective of customers, and as a sales plan for sales organizations. A strategic allocation algorithm includes three methods depending on FIXED RATIO, RANK and DEMAND BASIS. In addition, further topics would be discussed regarding the method of system implementation utilizing strategic allocation algorithms and information flow with an aim to integrate such a sales plan into the e-Biz. This study aims to provide a new solution in order to secure emerging competitive factors in today's enterprise world; that is, an achievement of faster business processes. It is suggested that this new solution be implemented in order to achieve an efficient business environment by systemizing the decision making process which in the past was manually conducted.

• The KIPS Transactions:PartD
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• v.17D no.4
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• pp.311-316
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• 2010

This paper presents a weight adjusted association rule mining algorithm (WARM). Assigning weights to each strategic factor and normalizing raw scores within each strategic factor are the key ideas of the presented algorithm. It is an extension of the earlier algorithm TSAA (transitive support association Apriori) and strategic importance is reflected by considering factors such as profit, marketing value, and customer satisfaction of each item. Performance analysis based on a real world database has been made and comparison of the mining outcomes obtained from three association rule mining algorithms (Apriori, TSAA, and WARM) is provided. The result indicates that each algorithm gives distinct and characteristic behavior in association rule mining.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.330-330
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• 2000

In this paper, as an entertainment robot the implementation of boxing robot system is presented for mechatronics education. In order for students to learn robot as a mechatronics system, boxing robot is a good model. The boxing robot consists of three parts: two link arms for punching, controller for actuating wheeled mobile robot, infrared rays sensors for the detection of he other robot and ring. The strategic algorithm for playing boxing is presented as wel as simple game rules.

• Journal of Navigation and Port Research
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• v.37 no.3
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• pp.321-327
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• 2013

As the market of express delivery services expands rapidly, delivery service companies are exposed to severe competition. As a result of the surplus of delivery companies, they are struggling with remaining competitive at a reasonable price with appropriate level of customer satisfaction. To cope with competition pressures, a strategic alliance is suggested as an effective solution to the challenges faced by small and medium enterprises (SMEs) in express delivery services. Therefore, this study suggests a combined optimization and simulation approach to the reconfiguration of an express delivery service network for strategic alliance with respect to strategy partnership of closing/keeping service centers among companies involved and adjustments of their cutoff times. An illustrative numerical example is presented to demonstrate the practicality and efficiency of the approach.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.495-498
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• 2005

The study is aimed at searching algorithm upgrading which can automatically compose goods displayed according to the degree of popularity regarding customer's requests, for the purpose of design of an intellectual shopping mall on the net and putting it into force by using classified technical Data-mining and statical analysis including personal information , entrance records and purchase records. This is for the study of strategic marketing. The system can automate the conventional shopping mall system by manual and personal judgements and also suggest a new formation of marketing techniques to strengthen the competition in B2B market which is steeply increasing.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.2
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• pp.577-594
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• 2020

Service Function Chaining (SFC) supports services through linking an ordered list of functions. There may be multiple instances of the same function, which provides a challenge to select available instances for all the functions in an SFC and generate a specific Service Function Path (SFP). Aiming to solve the problem of SFP selection, we propose an architecture consisting of distributed SFP algorithm and central control mechanism. Nodes generate distributed routings based on the first function and destination node in each service request. Controller supervises all of the distributed routing tables and modifies paths as required. The architecture is scalable, robust and quickly reacts to failures because of distributed routings. Besides, it enables centralized and direct control of the forwarding behavior with the help of central control mechanism. Simulation results show that distributed routing tables can generate efficient SFP and the average cost is acceptable. Compared with other algorithms, our design has a good performance on average cost of paths and load balancing, and the response delay to service requests is much lower.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.4
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• pp.1128-1145
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• 2022

Owing to the rapid development of information science, data analysis based on machine learning has become an interdisciplinary and strategic area. Marine predators algorithm (MPA) is a novel metaheuristic algorithm inspired by the foraging strategies of marine organisms. Considering the randomness of these strategies, an improved algorithm called co-evolutionary cultural mechanism-based marine predators algorithm (CECMPA) is proposed. Through this mechanism, search agents in different spaces can share knowledge and experience to improve the performance of the native algorithm. More specifically, CECMPA has a higher probability of avoiding local optimum and can search the global optimum quickly. In this paper, it is the first to use CECMPA to perform feature subset selection and optimize hyperparameters in support vector machine (SVM) simultaneously. For performance evaluation the proposed method, it is tested on twelve datasets from the university of California Irvine (UCI) repository. Moreover, the coronavirus disease 2019 (COVID-19) can be a real-world application and is spreading in many countries. CECMPA is also applied to a COVID-19 dataset. The experimental results and statistical analysis demonstrate that CECMPA is superior to other compared methods in the literature in terms of several evaluation metrics. The proposed method has strong competitive abilities and promising prospects.

• Journal of Korea Game Society
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• v.16 no.4
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• pp.79-86
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• 2016

Monte-Carlo Tree Search(MCTS) is a best-first tree search algorithm and has been successfully applied to various games, especially to the game of Go. We evaluate the performance of MCTS playing against each other in the game of Tic-Tac-Toe. It reveals that the first player always has an overwhelming advantage to the second player; and we try to find out the reason why the first player is superior to the second player in spite of the fact that the best game result should be a draw. Since MCTS is a statistical algorithm based on the repeated random sampling, it cannot adequately tackle an urgent problem that needs a strategy, especially for the second player. For this, we propose a strategic MCTS(S-MCTS) and show that the S-MCTS player never loses a Tic-Tac-Toe game.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.4
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• pp.322-329
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• 2005

This paper considers the application of mobile robot to the herding problem. The herding problem involves a ‘pursuer’ trying to herd a moving ‘evader’ to a predefined location. In this paper, two mobile robots act as pursuer and evader in the fenced area, where the pursuer robot uses a fuzzy cooperative decision strategy (FCDS) in the herding algorithm. To herd evader robot to a predefined position, the pursuer robot calculates strategic herding point and then navigates to that point using FCDS. FCDS consists of a two-level hierarchy: low level motion descriptors and a high level coordinator. In order to optimize the FCDS, we use the multi­thread evolutionary programming algorithm. The proposed algorithm is implemented in the real mobile robot system and its performance is demonstrated using experimental results.