• Journal of the Korea Society of Computer and Information
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• v.19 no.3
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• pp.45-54
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• 2014

In this paper, an improved two-step P2P traffic classification scheme is proposed to overcome the limitations of the existing methods. The first step is a signature-based classifier at the packet-level. The second step consists of pattern heuristic rules and a statistics-based classifier at the flow-level. With pattern heuristic rules, the accuracy can be improved and the amount of traffic to be classified by statistics-based classifier can be reduced. Based on the analysis of different decision tree algorithms, the statistics-based classifier is implemented with REPTree. In addition, the ensemble algorithm is used to improve the performance of statistics-based classifier Through the verification with the real datasets, it is shown that our hybrid scheme provides higher accuracy and lower overhead compared to other existing schemes.

• Journal of Information Technology Applications and Management
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• v.12 no.4
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• pp.1-12
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• 2005

In general, other conventional researches propose the fuzzy Petri net-based fuzzy reasoning algorithms based on the exhaustive search algorithms. If it can allow the certainty factors representing in the fuzzy production rules to use as the heuristic information, then it can allow the reasoning of rule-based systems to perform fuzzy reasoning in more effective manner. This paper presents a fuzzy Petri net(FPN) model to represent the fuzzy production rules of a rule-based system. Based on the fuzzy Petri net model, a weighted fuzzy reasoning algorithm is proposed to Perform the fuzzy reasoning automatically, This algorithm is more effective and more intelligent reasoning than other reasoning methods because it can perform fuzzy reasoning using the certainty factors which are provided by domain experts as heuristic information

• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.34-36
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• 1991

The idea of expert control is to incoporate a rule based expert system in a feedback control system. In this paper, we present some heuristic rules about input requlation and supervision and turning for D.C servo motor speed control in variable. The expert auto-turning PID controller which heuristic rules are used as an element of the feedback control system is implemented with the numerical algorithms and heuristic logics. The accurate control function is confirmed by computer simulation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.16 no.9
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• pp.877-882
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• 1991

The idea of expert control is to incoporate a rule based expert system in a feedback control system. In this paper, We present some heuristic rules about input regulation and supervision and turning for D.C. servo motor speed control. The expert auto-turning PID Controller which Heuristic rules are used as an element of the feedback control system is implemented with the numerical algorithms and Heuristic logics. The robust and accurate control function is confirmed by computer simulation..

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.9
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• pp.531-538
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• 2005

This paper proposes an expert system which is able to enhance the accuracy and productivity by determining the test strategy based on heuristic rules for test of the hybrid electronic circuit board producted massively in production line. The test heuristic rules are obtained from test system designer, test experts and experimental results. The guarding method separating the tested device with circumference circuit of the device is adopted to enhance the accuracy of measurements in the test of analog devices. This guarding method can reduce the error occurring due to the voltage drop in both the signal input line and the measuring line by utilizing heuristic rules considering the device impedance and the parallel impedance. Also, PSA(Parallel Signature Analysis) technique Is applied for test of the digital devices and circuits. In the PSA technique, the real-time test of the high integrated device is possible by minimizing the test time forcing n bit output stream from the tested device to LFSR continuously. It is implemented in Visual C++ computer language for the purpose of the implementation of the inference engine using the dynamic memory allocation technique, the interface with the electronic circuit database and the hardware direct control. Finally, the effectiveness of the builded expert system is proved by simulating the several faults occurring in the mounting process the electronic devices to the surface of PCB for a typical hybrid electronic board and by identifying the results.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 1998.10a
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• pp.309-313
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• 1998

Delay time of receiving and delivery is one of important factors that should be considered in the evaluation of the customer service level of a container terminal. In this study, dispatching rules are tested with the objective of minimizing the service delay time for arriving outside trucks. A dynamic programming model is suggested for a static dispatching problem in which all the truck arrivals are known in advance. In order to overcome the excessive computational time of the dynamic programming technique, several heuristic rules are suggested that can be applied in practices. A simulation study is carried out to test the performances of the heuristic rules.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.43
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• pp.81-89
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• 1997

This study is concerned with the scheduling problems in flexible manufacturing systems(FMSs). The scheduling problem in FMSs is a complex one when the number of machines and jobs are increased. Thus, a heuristic method is recommended in order to gain near-optimal solutions in a practically acceptable time. The purpose of this study is to develope a machine and AGV dispatching algorithm. The proposed dispatching algorithm is a on-line scheduling algorithm considering the due date of parts and the status of the system in the scheduling process. In the new machine and AGV dispatching algorithm, a job priority is determined by LPT/LQS rules considering job tardiness. The proposed heuristic dispatching algorithm is evaluated by comparison with the existing dispatching rules such as LPT/LQS, SPT/LQS, EDD/LQS and MOD/LQS. The new dispatching algorithm is predominant to existing dispatching rules in 100 cases out of 100 for the mean tardiness and 89 cases out of 100 for the number of tardy jobs.

• Korean Management Science Review
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• v.13 no.3
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• pp.173-186
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• 1996

This paper presents an approach for classifying scheduling problems and selecting a heuristic rule to yield best solution in terms of certain performance measure(s). Classification parameters are employed from previous studies on job shop scheduling and project scheduling. Neural network is used for learning and estimating the performance of heuristic rules. In addition, multi-criteria decision making techniques are employed to combine the preferences for each performance measure and heuristic rule for the problems with multi-objectives.

• Journal of the military operations research society of Korea
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• v.36 no.3
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• pp.29-42
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• 2010

In this study, the weapon-target assignment problem arising in military application of operations research is considered. We reformulated the problem in order to simplify the solution methods based on genetic algorithms and heuristics. Since the problem is well known as NP-complete and cannot be solved in polynomial time, such solution methods have been widely used to obtain good solutions. Two chromosome representations--target number representation and permutation representation--in genetic algorithm are compared. In addition, a construction heuristic and three improving heuristics are developed. Several experiments under the condition of transitivity rules in weapon's kill probability have been accomplished. It shows that the construction heuristic and exchange-based improving heuristic guarantees good solutions within a second and the performance of construction heuristic is sensitive to transitivity rules.

• Proceedings of the IEEK Conference
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• 2001.06c
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• pp.59-62
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• 2001

This paper discusses a data mining technique for time series analysis of traffic data, which provides useful knowledge for network configuration management. Commonly, a network designer must employ a combination of heuristic algorithms and analysis in an interactive manner until satisfactory solutions are obtained. The problem of heuristic algorithms is that it is difficult to deal with large networks and simplification or assumptions have to be made to make them solvable. Various data mining techniques are studied to gain valuable knowledge in large and complex telecommunication networks. In this paper, we propose a traffic pattern association technique among network nodes, which produces association rules of traffic fluctuation patterns among network nodes. Discovered rules can be utilized for improving network topologies and dynamic routing performance.