• Nonlinear Functional Analysis and Applications
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• 제26권3호
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• pp.611-628
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• 2021

In this paper, we propose a new branch-reduction-and-bound algorithm to solve the nonlinear knapsack problems by using general discrete monotonic optimization techniques. The specific properties of the problem are exploited to increase the efficiency of the algorithm. Computational experiments of the algorithm on problems with up to 30 variables and 5 different constraints are reported.

• 컴퓨터교육학회논문지
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• 제6권3호
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• pp.1-8
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• 2003

본 논문에서는 O(NlogN) 의 시간 복잡도와 데이터의 분포상태에 영향을 받지 않는 정보블록 정렬알고리즘(IBSA : Information Block Sort Algorithm)을 제안하고, 시뮬레이터를 이용하여 그 성능을 평가하였다. 2백만 개의 랜덤 데이터를 이용하여 IBSA의 성능을 측정해본 결과, 퀵 정렬의 22%, 개선된 퀵 정렬의 36% 정도의 비교회수만으로도 정렬할 수 있음을 보여주었다.

• 한국컴퓨터정보학회논문지
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• 제20권5호
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• pp.151-159
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• 2015

알고리즘은 문제를 효과적이고 효율적으로 해결하기 위해 필요한 문제 해결 과정을 설계하는 기법을 다루기 때문에 컴퓨터 과학을 배우는 사람이라면 반드시 학습해야 하는 영역이다. 알고리즘 교육은 학습자들이 알고리즘을 설계하는 기법을 익히는 것 뿐 아니라 학습한 알고리즘 기법을 문제를 해결하는 데 적절히 활용할 수 있는 능력을 함께 익힐 때 효과적이다. 특히 사회적으로 커다란 영향을 미칠 가능성을 가진 정보 영재 학생들을 대상으로 하는 교육 활성화에 대한 인식이 확산되기 시작하면서 이들을 어떻게 가르칠 것인가에 대한 관심이 고조되고 있다. 따라서 본 연구에서는 정보 영재 학습자들이 알고리즘 설계 기법을 보다 쉽게 학습하고 문제를 해결하는 데 활용하는 방법을 익힐 수 있도록 하기 위하여 퍼즐을 도입하였다. 연구 결과 퍼즐 기반의 알고리즘 학습이 전통적인 알고리즘 학습 방법에 비해 학습자들에게 긍정적인 영향을 준 것을 확인할 수 있었다. 이러한 결과는 학습자들이 퍼즐 기반 알고리즘 학습을 통해 알고리즘 설계 기법을 적용하는 다양한 문제 해결 경험을 함으로써 흥미와 학습의 전이가 향상된 것이라 해석할 수 있다.

• Journal of Electrical Engineering and Technology
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• 제12권1호
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• pp.64-71
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• 2017

Considering the volatility, intermittent and random of photovoltaic (PV) generation systems, accurate forecasting of PV power output is important for the grid scheduling and energy management. In order to improve the accuracy of short-term power forecasting of PV systems, this paper proposes a prediction model based on environmental factors and support vector machine optimized by genetic algorithm (GA-SVM). In order to improve the prediction accuracy of this model, weather conditions are divided into three types, and the gray correlation coefficient algorithm is used to find out a similar day of the predicted day. To avoid parameters optimization into local optima, this paper uses genetic algorithm to optimize SVM parameters. Example verification shows that the prediction accuracy in three types of weather will remain at between 10% -15% and the short-term PV power forecasting model proposed is effective and promising.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권3호
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• pp.1083-1097
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• 2018

This paper presents a novel range-free localization algorithm based on quantum particle swarm optimization. The proposed algorithm is capable of estimating the distance between two non-neighboring sensors for multi-hop heterogeneous wireless sensor networks where all nodes' communication ranges are different. Firstly, we construct a new cumulative distribution function of expected hop progress for sensor nodes with different transmission capability. Then, the distance between any two nodes can be computed accurately and effectively by deriving the mathematical expectation of cumulative distribution function. Finally, quantum particle swarm optimization algorithm is used to improve the positioning accuracy. Simulation results show that the proposed algorithm is superior in the localization accuracy and efficiency when used in random and uniform placement of nodes for heterogeneous wireless sensor networks.

• 한국운동역학회지
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• 제23권1호
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• pp.45-51
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• 2013

The current study developed the analysis program by employing the Polygon Clipping Algorithm to calculate the open area on the court when players try to spike a ball. The program consists of two kinds of output screen. First, on the main output screen, it is possible to calculate both blocked area by net and blockers, and opened area to avoid the blocked area when players spike the ball. Additionally, the secondary output screen shows the moving path of setter and the location of set. Main output screen indicates hitting points of spiking, blocking, and open area. Also, it is possible to analyze the movement of setter, location of set, and hitting point of attacker. The program was tested by comparing real coordinate value and location coordinate value which is operated on the program. To apply this program in the field, future study needs to develop the program that can calculate three dimensions coordinate fast by tracking the location of players or ball in real time.

• International Journal of Computer Science & Network Security
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• 제23권6호
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• pp.193-201
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• 2023

In this paper, we consider the maximum scatter traveling salesman problem (MSTSP), a travelling salesman problem (TSP) variant. The problem aims to maximize the minimum length edge in a salesman's tour that travels each city only once in a network. It is a very complicated NP-hard problem, and hence, exact solutions can be found for small sized problems only. For large-sized problems, heuristic algorithms must be applied, and genetic algorithms (GAs) are found to be very successfully to deal with such problems. So, this paper develops a hybrid GA (HGA) for solving the problem. Our proposed HGA uses sequential sampling algorithm along with 2-opt search for initial population generation, sequential constructive crossover, adaptive mutation, randomly selected one of three local search approaches, and the partially mapped crossover along with swap mutation for perturbation procedure to find better quality solution to the MSTSP. Finally, the suggested HGA is compared with a state-of-art algorithm by solving some TSPLIB symmetric instances of many sizes. Our computational experience reveals that the suggested HGA is better. Further, we provide solutions to some asymmetric TSPLIB instances of many sizes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권12호
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• pp.3416-3435
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• 2023

Task offloading in vehicular networks is hot topic in the development of autonomous driving. In these scenarios, due to the role of vehicles and pedestrians, task characteristics are changing constantly. The classical deep learning algorithm always uses a pre-trained neural network to optimize task offloading, which leads to system performance degradation. Therefore, this paper proposes a neural network fine-tuning task offloading algorithm, combining with location prediction for pedestrians and vehicles by the Payne model of fluid dynamics and the car-following model, respectively. After the locations are predicted, characteristics of tasks can be obtained and the neural network will be fine-tuned. Finally, the proposed algorithm continuously predicts task characteristics and fine-tunes a neural network to maintain high system performance and meet low delay requirements. From the simulation results, compared with other algorithms, the proposed algorithm still guarantees a lower task offloading delay, especially when congestion occurs.

• 공학논문집
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• 제1권1호
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• pp.49-57
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• 1997

본 논문에서는 Habermann의 deadlock 회피책에 대한 기존의 방안을 향상시킬 수 있는 방법을 고안하였다. 먼저 correction, efficiency, concurrency 측면에서 기존의 개선 방법들을 비교 분석한 다음, 대표적인 Kameda의 개선방안을 심도있게 논의한다. Dinic의 알고리듬을 채택한 Kamedia의 방법에서는 실행시간 O($mn^1.5$)이 요구되지만 Karzanov의 wave method를 응용하여 본고에서 제안한 faster algorithm에서는 실행시간 O($mn^1.5$)이 됨을 보인다.

• 한국전기전자재료학회논문지
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• 제32권1호
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• pp.13-19
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• 2019

This paper proposes an easy algorithm for finding tapped-delay-line (TDL) filter coefficients in an adaptive filter algorithm using orthogonal input signals. The proposed algorithm can be used to obtain the coefficients and errors of a TDL filter without using an inverse orthogonalization process for the orthogonal input signals. The form of the proposed algorithm in this paper has the advantages of being easy to use and similar to the familiar recursive least-squares (RLS) algorithm. In order to evaluate the proposed algorithm, system identification simulation of the $11^{th}$-order finite-impulse-response (FIR) filter was performed. It is shown that the convergence characteristics of the learning curve and the tracking ability of the coefficient vectors are similar to those of the conventional RLS analysis. Also, the derived equations and computer simulation results ensure that the proposed algorithm can be used in a similar manner to the Levinson-Durbin algorithm.