• The Pure and Applied Mathematics
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• v.14 no.3
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• pp.191-196
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• 2007

The main components in the generalized Mandelbrot sets are under a theoretical investigation for their parametric boundary equations. Using the boundary geometries, a fast construction algorithm is introduced for the generalized Mandelbrot set. This fast algorithm definitely reduces the construction CPU time in comparison with the naive algorithm. Its graphic implementation displays the mysterious and beautiful fractal sets.

• Nonlinear Functional Analysis and Applications
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• v.26 no.3
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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.

• Journal of the Korea Society of Computer and Information
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• v.20 no.5
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• pp.151-159
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• 2015

The algorithm in computer science includes skills to design a problem solving process for solving problems efficiently and effectively. Therefore all learners who learn computer science have to learn algorithm. Education for algorithm is effective when learners acquire skills to design algorithm as well as ability to use appropriate design skills solving problems. Especially since it is heightened people awareness to cultivating informatics gifted students who have potential of significant impact on society, many studies on how to teach them have been in progress. Therefore in this study we adopted puzzles to help informatics gifted students learn skills to design algorithm and how to use them to solve problems. The results of pre and post test compared to traditional algorithm learning, we identified that puzzled based algorithm learning gave a positive impact to students. Students had various problem solving experience applying algorithm design skills in puzzle based learning. As a result, students of learning and learning transfer has been improved.

• Journal of Electrical Engineering and Technology
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• v.12 no.1
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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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• v.17 no.12
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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.

• Korean Journal of Applied Biomechanics
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• v.23 no.1
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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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.3
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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.

• International Journal of Computer Science & Network Security
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• v.23 no.6
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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.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.32 no.1
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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.

• The Journal of Engineering Research
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• v.1 no.1
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• pp.49-57
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• 1997

In this paper, the follow-up works of Habermann's deadlock avoidance algorithm is investigated from the view of correction, efficiency and concurrency. Habermann's deadlock avoidance algorithm is briefly surveyed and in-depth discussion of follow-up algorithms modified and improved is presented. Then, further improvement of Kameda's algorithm will be discussed. His algorithm for testing deadlock-freedom in computer system converts the Habermann's model into a labeled bipartite graph so that the deadlock detection problem can be equivalent to finding complete matching for Mormon marriage problem. His algorithm has a running time of O($mn^1.5$) because Dinic's algorithm is used. The speed of above algorithm can be enhanced by employing a faster algorithm for finding a maximal matching. The wave method by Kazanov is used for.