• The Journal of the Korea Contents Association
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• v.5 no.5
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• pp.152-158
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• 2005

By using a combination of different feature sets extracted from input character patterns, we can improve the character recognition system performance. To reduce the dimensionality of the combined feature vector, we conduct the feature selection. This paper proposes a general framework for the feature combination and selection for character recognition problems. It also presents a specific design for the handwritten numeral recognition. Tn the design, DDD and AGD feature sets are extracted from handwritten numeral patterns, and a genetic algorithm is used for the feature selection. Experimental result showed a significant accuracy improvement by about 0.7% for the CENPARMI handwrittennumeral database.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.2
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• pp.231-235
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• 2004

According to revealing the DNA sequence of human and living things, it increases that a demand on a new computational processing method which utilizes DNA sequence information. In this paper we propose a classification algorithm based on negative selection of the immune system to classify DNA patterns. Negative selection is the process to determine an antigenic receptor that recognize antigens, nonself cells. The immune cells use this antigen receptor to judge whether a self or not. If one composes n group of antigenic receptor for n different patterns, they can classify into n patterns. In this paper we propose a pattern classification algorithm based on negative selection in nucleotide base level and amino acid level.

• ETRI Journal
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• v.40 no.5
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• pp.604-612
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• 2018

To solve the problem of unbalanced loads and the short network lifetime of heterogeneous wireless sensor networks, this paper proposes a node-selection algorithm based on energy balance and dynamic adjustment. The spacing and energy of the nodes are calculated according to the proximity to the network nodes and the characteristics of the link structure. The direction factor and the energy-adjustment factor are introduced to optimize the node-selection probability in order to realize the dynamic selection of network nodes. On this basis, the target path is selected by the relevance of the nodes, and nodes with insufficient energy values are excluded in real time by the establishment of the node-selection mechanism, which guarantees the normal operation of the network and a balanced energy consumption. Simulation results show that this algorithm can effectively extend the network lifetime, and it has better stability, higher accuracy, and an enhanced data-receiving rate in sufficient time.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.04a
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• pp.516-520
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• 1996

This paper focues on development of a timer selection algorithm for IEEE802.4 token bus networks to serve large-scale integrated manufacturing systems. Such factory automation networks have to satisfy delay constraints imposed on time-critical messages while maintaining as much network capacity as possible for non-time-critical messages. Therefore, the object of this paper is to develop timer selection algorithm to minimize a certain penalty function. This paper presents an algorithm based on Genetic Algorithm. The efficacy of the algorithm has been demonstrated by a series of simulation experiments.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.33A no.4
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• pp.18-26
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• 1996

In this paper we propose a new dual structured tap selection algorithm for voice echo canceller in digital cellular communication system, investigating adaptive filtering algorithms for echo cancellation in long distance telephony or mobile communication system. The proposed algorithm has a two-stage processing structure that after a dispersive region in an impulse response of an echo path is found out, the tap coefficients of a short length filter are adjusted adaptively for the region, because the impuse response has a very little portion of the dispersion. Simulation results show that the proposed algorithm with 256 taps gives a performance of convergence speed superior to both full-tap normalized least mean with 256 taps gives a performance of convergence speed superior to both full-tap normalized least mean square (NLMS) and a scrub taps waiting in a queue (STWQ) algorithms by about eighty per cent, also to a tap selection algorithm by about twenty per cent. And the resutls diplay that if the more tap coefficients are used due to a long delayed dispersive zone, the proposed algorithm produces the better performance.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.11
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• pp.1394-1400
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• 1999

This paper presents and efficient improvement of the iterative eigenvalue calculation method and the selection of initial values in AESOPS algorithm. To determine the initial eigenvalues of the system, system state matrix is constructed with the two-axis generator model. From the submatrices including synchronous and damping coefficients, the initial eigenvalues are calculated by the QR method. Participation factors are also calculated from the above submatrices in order to determine the generators which have a important effect to the specific oscillation mode. Also, the heuristically approximated eigenvalue calculation method in the AESOPS algorithm is transformed to the Newton Raphson Method which is largely used in the nonlinear numerical analysis. The new methods are developed from the AESOPS algorithm and thus only a few calculation steps are added to practice the proposed algorithm.

• Journal of Information Processing Systems
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• v.2 no.2
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• pp.130-134
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• 2006

In the distributed replicating server model, the provision of replicated services will improve the performance of the providing service and efficiency for clients. Efficiently composing the server selection algorithm decreases the retrieval time for replicated data. In this paper, we define the system model that selects and connects the replicated server that provides an optimal service using the server-side downstream measurement and propose a server selection algorithm.

• The Journal of Information Systems
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• v.26 no.3
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• pp.63-90
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• 2017

Purpose This study proposes a novel system trading model using case-based reasoning (CBR) based on absolute similarity threshold. The proposed model is designed to optimize the absolute similarity threshold, feature selection, and instance selection of CBR by using genetic algorithm (GA). With these mechanisms, it enables us to yield higher returns from stock market trading. Design/Methodology/Approach The proposed CBR model uses the absolute similarity threshold varying from 0 to 1, which serves as a criterion for selecting appropriate neighbors in the nearest neighbor (NN) algorithm. Since it determines the nearest neighbors on an absolute basis, it fails to select the appropriate neighbors from time to time. In system trading, it is interpreted as the signal of 'hold'. That is, the system trading model proposed in this study makes trading decisions such as 'buy' or 'sell' only if the model produces a clear signal for stock market prediction. Also, in order to improve the prediction accuracy and the rate of return, the proposed model adopts optimal feature selection and instance selection, which are known to be very effective in enhancing the performance of CBR. To validate the usefulness of the proposed model, we applied it to the index trading of KOSPI200 from 2009 to 2016. Findings Experimental results showed that the proposed model with optimal feature or instance selection could yield higher returns compared to the benchmark as well as the various comparison models (including logistic regression, multiple discriminant analysis, artificial neural network, support vector machine, and traditional CBR). In particular, the proposed model with optimal instance selection showed the best rate of return among all the models. This implies that the application of CBR with the absolute similarity threshold as well as the optimal instance selection may be effective in system trading from the perspective of returns.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.8A
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• pp.581-590
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• 2003

This paper proposes the routing path selection mechanism for source routing-based PtMP (Point-to-Multipoint) call in ATM switching system. Especially, it suggests PtMP routing path selection method that can share the maximum resource prior to the optimal path selection, guarantee the reduction of path calculation time and cycle prevention. The searching for the nearest branch point from destination node to make the maximum share of resource is the purpose of this algorithm. Therefore among neighbor nodes from destination node by back-tracking, this algorithm fixes the node crossing first the node on existing path having the same Call ID as branch node, constructs the optimal PtMP routing path. The optimal node to be selected by back-tracking is selected by the use of Dijkstra algorithm. That is to say, PtMP routing path selection performs the step of cross node selection among neighboring nodes by back-tracking and the step of optimal node selection(optimal path calculation) among neighboring nodes by back-tracking. This technique reduces the process of search of routing information table for path selection and path calculation, also solves the cycle prevention easily during path establishment.

• Journal of KIISE:Software and Applications
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• v.36 no.5
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• pp.396-400
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• 2009

During periods of large data transmission, routing selection methods are used to efficiently manage data traffic and improve the speed of transmission. One approach in routing selection is AntNet that applies the Ant algorithm in transmissions with uniform probability. However, this approach uses random selection, which can cause excessive data transmission rates and fail to optimize data This paper presents the use of the Genetic Algorithm (GA) to efficiently route and disperse data transmissions, during periods with "unnecessary weight increases for random selection". This new algorithm for improved performance provides highly accurate estimates of the transmission time and the transmission error rate.