• Journal of KIISE:Software and Applications
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• v.32 no.7
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• pp.674-682
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• 2005

This paper proposes classification of multi-spectral satellite image based on fusion of fuzzy G-K (Gustafson-Kessel) algorithm and PCM algorithm. The suggested algorithm establishes the initial cluster centers by selecting training data from each category, and then executes the fuzzy G-K algorithm. PCM algorithm perform using classification result of the fuzzy G-K algorithm. The classification categories are allocated to the corresponding category when the results of classification by fuzzy G-K algorithm and PCM algorithm belong to the same category. If the classification result of two algorithms belongs to the different category, the pixels are allocated by Bayesian maximum likelihood algorithm. Bayesian maximum likelihood algorithm uses the data from the interior of the average intracluster distance. The information of the pixels within the average intracluster distance has a positive normal distribution. It improves classification result by giving a positive effect in Bayesian maximum likelihood algorithm. The proposed method is applied to IKONOS and Landsat TM remote sensing satellite image for the test. As a result, the overall accuracy showed a better outcome than individual Fuzzy G-K algorithm and PCM algorithm or the conventional maximum likelihood classification algorithm.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.285-286
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• 2008

In this paper, we propose adaptive search channel estimate algorithm. The proposed algorithm is modified LMS algorithm which has a variable step size and parallel convolution. In simulation result, a error estimate accuracy of the proposed algorithm is about -20 dB and general LMS algorithm is about 10 dB. The proposed algorithm is better error estimate accuracy than general LMS algorithm.

• Journal of the military operations research society of Korea
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• v.6 no.1
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• pp.119-124
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• 1980

An efficient algorithm which can be employed in obtaining the minimal cut sets of a fault tree containing repeated events is introduced. A sample fault tree illustrates this algorithm. Efficiency of an algorithm is defined as the ratio of the number of minimal cut sets to the number of cut sets determined by the algorithm. An efficiency of the proposed algorithm is compared with those of two existing algorithms : Fussell and Vesely's algorithm and Bengiamin et al. 's algorithm. The proposed algorithm is shown to be more efficient than the existing two algorithms.

• Journal of the military operations research society of Korea
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• v.26 no.1
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• pp.47-55
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• 2000

The purpose of this paper is to develop a new heuristic algorithm for vehicle routing problem. The algorithm is composed of two steps. First step is to make a initial solution using sweeping algorithm. Second step is to improve initial solution for optimal solution using node exchange algorithm and tabu search algorithm. We have proven that our algorithm has produced better results than solutions obtained by saving algorithm and genetic in ten example problems with different unit size.

• Proceedings of the Korean Information Science Society Conference
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• 2006.10a
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• pp.490-493
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• 2006

본 논문은 Linux Cluster의 MPICH에서 MPI_Allgather Algorithm의 성능을 개선하고 실험을 통해 최대 30%의 성능향상을 증명하였다. MPICH의 기존 버전이 메시지의 크기와 실행 프로세스 수에 따라 Recursive Doubling, Bruck Algorithm, Ring Algorithm을 차등 적용했던 것을, 앞의 Algorithm을 개선하여 Double Bruck Algorithm, Double Ring Algorithm을 제안, 구현하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.6
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• pp.2554-2580
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• 2018

Lenstra-Lenstra-$Lov{\acute{a}}sz$ (LLL) is an effective receiving algorithm for Multiple-Input-Multiple-Output (MIMO) systems, which is believed can achieve full diversity in MIMO detection of fading channels. However, the LLL algorithm features polynomial complexity and shows poor performance in terms of convergence. The reduction of algorithmic complexity and the acceleration of convergence are key problems in optimizing the LLL algorithm. In this paper, a variant of the LLL algorithm, the Hybrid-Fix-and-Round LLL algorithm, which combines both fix and round measurements in the size reduction procedure, is proposed. By utilizing fix operation, the algorithmic procedure is altered and the size reduction procedure is skipped by the hybrid algorithm with significantly higher probability. As a consequence, the simulation results reveal that the Hybrid-Fix-and-Round-LLL algorithm carries a faster rate of convergence compared to the original LLL algorithm, and its algorithmic complexity is at most one order lower than original LLL algorithm in real field. Comparing to other families of LLL algorithm, Hybrid-Fix-and-Round-LLL algorithm can make a better compromise in performance and algorithmic complexity.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.9B
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• pp.1039-1048
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• 2011

Carrier Ethernet, which extend The algorithm based on constructing the mixed topology and performing link stretching, MT/s, has been proposed for designing cost-efficient Carrier Ethernet in optical network with multi-line-rate. However, the MT/s algorithm has high blocking ratio because the wavelength capacity is fully allocated without considering the load balance of network. In this paper, we propose an efficient mixed topology configuration (EMTC) algorithm by modifying MT/s algorithm. In order to reduce blocking ratio, we adapt a threshold for each link to restrict the link utilization so that traffic load can be distributed over whole network. We also apply the EMTC algorithm into optical hybrid switched network to evaluate the availability of our algorithm for different applications. The performance of the EMTC algorithm is compared with that of MT/s algorithm through OPNET simulation. The simulation results show that our algorithm achieve lower blocking ratio than the MT/s algorithm. Moreover, in hybrid switched network, our algorithm performs better than MT/s algorithm in terms of packet loss ratio and end-to-end delay.

• Journal of the Korea Society of Computer and Information
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• v.12 no.2 s.46
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• pp.131-139
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• 2007

This paper proposed a multi-resolution algorithm. Its search point and complexity were compared with those of block match algorithm. Also the speed up comparison was made with the block match algorithm. The proposed multi-resolution NTSS-3 Level algorithm was compared again with its targets, TSS-3 Level algorithm and NTSS algorithm. The comparison results showed that the NTSS-3 Level algorithm was superior in search point and speed up. Accordingly, the proposed NTSS-3 Level algorithm was two to three times better in search point and two to four times better in complexity calculation than those of the compared object, the block match algorithm. In speed up, the proposed NTSS-3 Level algorithm was two times better. Accordingly, the proposed multi-resolution NTSS-3 Level algorithm showed PSNR ration portion excellency in search point and speed up.

• Journal of the Korea Society of Computer and Information
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• v.17 no.9
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• pp.139-147
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• 2012

This paper suggests simple search algorithm for optimal solution in assignment problem. Generally, the optimal solution of assignment problem can be obtained by Hungarian algorithm. The proposed algorithm reduces the 4 steps of Hungarian algorithm to 1 step, and only selects the minimum cost of row and column then gets the optimal solution simply. For the 27 balanced and 7 unbalanced assignment problems, this algorithm finds the optimal solution but the genetic algorithm fails to find this values. This algorithm improves the time complexity O($n^3$) of Hungarian algorithm to O(n). Therefore, the proposed algorithm can be general algorithm for assignment problem replace Hungarian algorithm.

• Journal of Information Processing Systems
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• v.18 no.6
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• pp.719-728
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• 2022

The prediction of short-term traffic flow is the theoretical basis of intelligent transportation as well as the key technology in traffic flow induction systems. The research on short-term traffic flow prediction has showed the considerable social value. At present, the support vector regression (SVR) intelligent prediction model that is suitable for small samples has been applied in this domain. Aiming at parameter selection difficulty and prediction accuracy improvement, the artificial bee colony (ABC) is adopted in optimizing SVR parameters, which is referred to as the ABC-SVR algorithm in the paper. The simulation experiments are carried out by comparing the ABC-SVR algorithm with SVR algorithm, and the feasibility of the proposed ABC-SVR algorithm is verified by result analysis. Continuously, the simulation experiments are carried out by comparing the ABC-SVR algorithm with particle swarm optimization SVR (PSO-SVR) algorithm and genetic optimization SVR (GA-SVR) algorithm, and a better optimization effect has been attained by simulation experiments and verified by statistical test. Simultaneously, the simulation experiments are carried out by comparing the ABC-SVR algorithm and wavelet neural network time series (WNN-TS) algorithm, and the prediction accuracy of the proposed ABC-SVR algorithm is improved and satisfactory prediction effects have been obtained.