• The KIPS Transactions:PartD
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• v.14D no.3 s.113
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• pp.285-292
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• 2007

There has been an increasing interest in n since it is spotlighted as the standard for data representation and exchange in the Web. The structural information for XML documents serves several important purposes. In spite of its importance, the schema is not mandatory for XML documents. Thus, much research to extract structural information for XML document has been conducted. In this paper, we present a technique for efficient extraction of concise and accurate DTD for XML documents. By restriction of DTD content model using the mixed content model of DTD and XML Schema as well as applying some heuristic rules proposed in this paper, we achieve the efficiency and conciseness. The result of an experiment with real life DTDs shows that our approach is superior to existing approaches.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.3
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• pp.110-117
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• 2009

This paper introduces a case study for efficient generation of production schedules in a tube manufacturing system. The considered scheduling problem consists of two sub problems : lot sizing for a job and Job sequencing. Since these problems require simulation optimization in which the performance measures are obtained by simulation execution, the trade-off between solution quality and computation time is an important issue. In this study, the optimal lot size for every product type is determined from simulation experiments. Then, target production quantity for each product type is transformed to several jobs such that a Job consists of determined lot size. To obtain the good solution for a Job sequence in a reasonable time, a number of alternatives are generated from heuristic rules developed by intuition and analysis of the considered system, and a job sequence is selected from simulation experiments.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.2
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• pp.397-406
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• 2000

Genetic algorithm is used as a means of search, optimization md machine learning, its structure is simple but it is applied to various areas. And it is about an active and effective controller which can flexibly prepare for changeable circumstances. For this study, research about an action base system evolving by itself is also being considered. There is to have a problem that depended entirely on heuristic knowledge of expert forming membership function and control rule for fuzzy controller design. In this paper, for forming the fuzzy control to perform self-organization, we tuned the membership function to the most optimal using a genetic algorithm(GA) and improved the control efficiency by the self-correction and generation of control rules.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.53 no.10
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• pp.565-572
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• 2004

This paper proposes an expert system which can enhance the accuracy of real-time bus reconfiguration strategy by adopting local minimum tree search method and minimize the spreading effect of the fault by considering totally the operating condition when a main transformer fault occurs in the automated substation. The local minimum tree search method to expand the best-first search method. This method has an advantage which can improve the performance of solution within the limits of the real-time condition. The inference strategy proposed expert system consists of two stages. The first stage determines the switching candidate set by searching possible switching candidates starting from the main transformer or busbar related to the event. And, second stage determines the rational real-time bus reconfiguration strategy based on heuristic rules for the obtained switching candidate set. Also, this paper studies the generalized distribution substation modelling using graph theory and a substation database is designed based on the study result. The inference engine of the expert system and the substation database is implemented in MFC function of Visual C++. Finally, the performance and effectiveness of the proposed expert system is verified by comparing the best-first search solution and local minimum tree search solution based on diversity event simulations for typical distribution substation.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.6 no.3
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• pp.190-196
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• 2006

In this paper, the nonlinear damping force model is made to identify the properties of the ER damper using higher order spectrum. The higher order spectral analysis is used to investigate the nonlinear frequency coupling phenomena with the damping force signal according to the sinusoidal excitation of the damper. Also, this paper presents an inverse model of the ER damper, i.e., the model can predict the required voltage so that the ER damper can produce the desired force for the requirement of vibration control of vehicle suspension systems. The inverse model has been constructed by using piecewise linear damping force model. In this paper, the fuzzy logic control based on heuristic knowledge is combined with the skyhook control. And it is simulated for a quarter car model. The acceleration of the sprung mass is included in the premise part of the fuzzy rules to reduce the vertical acceleration RMS value of the sprung mass. Then scaling factors and membership functions are tuned using genetic algorithm to obtain optimal performance.

• 한국지구물리탐사학회:학술대회논문집
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• 2003.11a
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• pp.176-183
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• 2003

This paper presents a neural network based approach to disseminating information relating to experimental and field observations in engineering. Although the methodology is generic and can be applied to many areas of engineering science, attention is focussed here solely on geotechnical engineering applications. Field data relating to the settlement of foundations presented by Burland and Burbidge (1985) which led to their well known equation for calculation of settlement, now included in most text books, is re-visited. A part of the data, chosen randomly, is used to train an Artificial Neural Network (ANN), which relates foundation settlement to various causes as identified by the authors. Predictions are made for situations for which data were not used in training. These indicate sufficient accuracy when compared to the original field data. Accuracy of predictions is further improved when all the data are included in the training set. The finally trained ANN is shown to represent these data more accurately than the Burland and Burbidge equation. Based on the above heuristic example, an ANN is presented as an alternative to developing equations and design rules in geotechnical engineering practice. Significant advantages are shown to arise by using this methodology. Ease of updating the ANN, as and when additional data becomes available, being the most important one. Loss of transparency, however, seems to be the main disadvantage.

• Journal of KIISE
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• v.42 no.11
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• pp.1452-1458
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• 2015

Korean Morphological Analysis is a difficult process. Because Korean is an agglutinative language, one of the most important processes in Morphological Analysis is Morpheme Recovery. There are some methods using Heuristic rules and Pre-Analyzed Partial Words that were examined for this process. These methods have performance limits as a result of not using contextual information. In this study, we built a Korean morpheme recovery system using deep learning, and this system used word embedding for the utilization of contextual information. In '들/VV' and '듣/VV' morpheme recovery, the system showed 97.97% accuracy, a better performance than with SVM(Support Vector Machine) which showed 96.22% accuracy.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.2
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• pp.145-152
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• 1999

This paper presents an optimal design method for fuzzy logic controllers using genetic algorithms. In general, the design of fuzzy logic controllers has difficulties in the acquisition of exper's knowledge and relies to a great extent on empirical and heuristic knowledge which, in many cases, cannot be objectively justified. So, the performance of the controller can be degraded in the case of plant parameter variations or unpredictable incident which the designer may have ignored, and parameters of the fuzzy logic controller obtained by expert's control action may not be global. To solve these problems, the proposed method using genetic algorithms in this paper, can tune the parameters of fuzzy logic controller including scaling factors and determine the appropriate number of fuzzy reles systematically and automatically. We provide the second drder dead time plant and inverted pendulum system to evaluate the feasibility and generality of our proposed method. Comparison shows that the proposed controller can producd higher accuracy and a smaller number of fuzzy rules than manually tuned fuzzy logic controller.

• Management Science and Financial Engineering
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• v.17 no.1
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• pp.79-94
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• 2011

Team orienteering, an extension of single-competitor orienteering, is the problem of determining multiple paths from a starting node to a finishing node for a given allowed time or distance limit fixed for each of the paths with the objective of maximizing the total collected score. Each path is through a subset of nodes, each of which has an associated score. The team orienteering problem has many applications such as home fuel delivery, college football players recruiting, service technicians scheduling, military operations, etc. Unlike existing optimal and heuristic algorithms often leading to heavy computation, this paper suggests two types of priority rule based heuristics-serial and parallel ones-that are especially suitable for practically large-sized problems. In the proposed heuristics, all nodes are listed in an order using a priority rule and then the paths are constructed according to this order. To show the performances of the heuristics, computational experiments were done on the small-to-medium sized benchmark instances and randomly generated large sized test instances, and the results show that some of the heuristics give reasonable quality solutions within very short computation time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.12
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• pp.5948-5971
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• 2019

Estimating loss rates with the packet traces captured from some point in the middle of the network has received much attention within the research community. Meanwhile, existing intermediate-point methods like [1] require the capturing system to capture all the TCP traffic that crosses the border of an access network (typically Gigabit network) destined to or coming from the Internet. However, limited to the performance of current hardware and software, capturing network traffic in a Gigabit environment is still a challenging task. The uncaptured packets will affect the total number of captured packets and the estimated number of packet losses, which eventually affects the accuracy of the estimated loss rate. Therefore, to obtain more accurate loss rate, a method of strengthening packet loss measurement from the network intermediate point is proposed in this paper. Through constructing a series of heuristic rules and leveraging the binomial distribution principle, the proposed method realizes the compensation for the estimated loss rate. Also, experiment results show that although there is no increase in the proportion of accurate estimates, the compensation makes the majority of estimates closer to the accurate ones.