• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.3
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• pp.441-446
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• 2010

Each robot decides and behaviors themselves surrounding circumstances in the swarm robot system. Robots have to conduct tasks allowed through cooperation with other robots. Therefore each robot should have the ability to learn and evolve in order to adapt to a changing environment. In this paper, we proposed learning based on Q-learning algorithm and evolutionary using Harmony Search algorithm and are trying to improve the accuracy using Harmony Search Algorithm, not the Genetic Algorithm. We verify that swarm robot has improved the ability to perform the task.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.5
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• pp.1084-1090
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• 2015

In this paper, we propose a Tabu search algorithm to efficiently deploy the sensor nodes for maximizing the network sensing coverage in wireless sensor networks. As the number of the sensor nodes in wireless sensor networks increases, the amount of calculation for searching the solution would be too much increased. To obtain the best solution within a reasonable execution time in a high-density network, we propose a Tabu search algorithm to maximize the network sensing coverage. In order to search effectively, we propose some efficient neighborhood generating operations of the Tabu search algorithm. We evaluate those performances through some experiments in terms of the maximum network sensing coverage and the execution time of the proposed algorithm. The comparison results show that the proposed algorithm outperforms other existing algorithms.

• Journal of Broadcast Engineering
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• v.12 no.3
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• pp.278-288
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• 2007

We propose the fast full search algorithm that reduces the computational load of the block matching algorithm which is used for a motion estimation in the video coding. Since the conventional spiral search method starts searching at the center of the search window and then moves search point to estimate the motion vector pixel by pixel, it is good for the slow motion picture. However we proposed the efficient motion estimation method which is good for the fast and slow motion picture. Firstly, when finding the initial threshold value, we use the expanded predictor that can approximately calculate minimum threshold value. The proposed algorithm estimates the motion in the new search order after partitioning the search window and adapt the directional search order in the re-divided search window. At the result, we can check that the proposed algorithm reduces the computational load 94% in average compared to the conventional spiral full search algorithm without any loss of image quality.

• Journal of Navigation and Port Research
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• v.47 no.6
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• pp.401-409
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• 2023

This study compared and analyzed the performance of a distributed area search algorithm and a distributed probability search algorithm based on information exchange between ships. The distributed algorithm is a method that can search for an optimal avoidance route based on information exchange between ships. In the distributed area search algorithm, only a ship with the maximum cost reduction among neighboring ships has priority, so the next expected location can be changed. The distributed stochastic search algorithm allows a non-optimal value to be searched with a certain probability so that a new value can be searched. A circular-based ship collision avoidance model was used for the ship-to-ship collision avoidance experiment. The experimental method simulated the distributed area search algorithm and the distributed stochastic search algorithm while increasing the number of ships from 2 to 50 that were the same distance from the center of the circle. The calculation time required for each algorithm, sailing distance, and number of message exchanges were compared and analyzed. As a result of the experiment, the DSSA(Distributed Stochastic Search Algorithm) recorded a 25%calculation time, 88% navigation distance, and 84% of number of message exchange rate compared to DLSA.

• The Transactions of the Korea Information Processing Society
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• v.4 no.10
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• pp.2470-2476
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• 1997

We propose a new real-time search algorithm and provide experimental evaluation and comparison of the new algorithm with mini-min lookahead algorithm. Many other real-time heuristic-search approached often divide the problem space to several sub-problems. In this paper, the proposed algorithm guarantees not only the sub-problem deadline but also total deadline. Several heuristic real-time search algorithms such as $RTA^{\ast}$, SARTS and DYNORA have been proposed. The performance of such algorithms depend on the quality of their heuristic functions, because such algorithms estimate the search time based on the heuristic function. In real-world problem, however, we often fail to get an effective heuristic function beforehand. Therefore, we propose a new real-time algorithm that determines the sub-problem deadline based on the status of search space during sub-problem search process. That uses the cut-off method that is a dynamic stopping-criterion-strategy to search the sub-problem.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.8
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• pp.1649-1655
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• 2005

For systems with coexisting cellular and hot-spot cells in broadband orhogonal frequency and code division multiplexing (OFCDM) systems, a suitable cell search algorithm is proposed fur the common pilot channel (CPICH) in the forward link using separated I/Q channel cell specific codes(CSSC), in which the cellular cell specific scrambling code (CCSSC) is assigned to the in-phase (Q) pilot channel of all cellular cells, and the exclusive hot-spot cell specific scrambling code (HSCSSC) group is assigned to the quadrature (Q) pilot channel of all hot-spot cells. Therefore, the proposed algorithm enables a mobile station (MS) to search quickly for the most desirable hot-spot cell due to reducing the effect of CCSSC, when a MS wants to use a mobile internet. The computer simulation results show that the proposed cell search algorithm can achieve faster cell search time performance, compared to conventional cell search methods.

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.7
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• pp.448-453
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• 2006

We extend a parallel depth-first search (DFS) algorithm for planar graphs to deal with (non-planar) solid grid graphs, a subclass of non-planar grid graphs. The proposed algorithm takes time O(log n) with $O(n/sqrt{log\;n})$ processors in Priority PRAM model. In our knowledge, this is the first deterministic NC algorithm for a non-planar graph class.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.10
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• pp.786-790
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• 2009

In this paper, we present a new heuristic search algorithm, HSCP, that can solve conditional/contingent planning problems with nondeterministic actions as well as partial observations. The algorithm repeats its AND-OR search trials until a complete solution graph can be found. However, unlike existing heuristic AND-OR search algorithms such as$AO^*$ and $LAO^*$, the AND-OR search trial conducted by HSCP concentrates on only a single candidate of solution subgraphs to expand it into a complete solution graph. Moreover, unlike real-time dynamic programming algorithms such as RTDP and LRTDP, the AND-OR search trial of HSCP finds a solution immediately when it possible without delaying it until the estimated value of every state converges. Therefore, the HSCP search algorithm has the advantage that it can find a sub-optimal conditional plan very efficiently.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.3
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• pp.594-600
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• 2017

This paper proposes a global search based motion estimation algorithm for high performance HEVC encoder and its hardware architecture. To eliminate temporal redundancy, motion estimation in HEVC inter-view prediction uses global search and fast search algorithm to search for a predicted block having a high correlation with the current PU in an interpolated reference picture. The global search method predicts the motion of all candidate blocks in a given search area, thus ensuring optimal results, but has a disadvantage of large computation time. Therefore we propose a new algorithm that reduces computational complexity by reusing SAD operation in global search to reduce computation time of inter prediction. As a result of applying the proposed algorithm to standard software HM16.12, the computation time was reduced by 61%, BDBitrate by 11.81%, and BDPSNR by about 0.5% compared with the existing search algorithm. As a result of hardware design, the maximum operating frequency is 255 MHz and the total number of gates is 65.1K.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.3
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• pp.401-406
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• 2011

In order to solve a complex optimization problem more efficiently than traditional approaches, various meta-heuristic algorithms such as genetic algorithm, ant-colony algorithm, and harmony search algorithm have been extensively researched. Compared with other meta-heuristic algorithm, harmony search algorithm shows a better result to resolve the complex optimization issues. Harmony search algorithm is inspired by the improvision process of musician for most suitable harmony. In general, the performance of harmony search algorithm is determined by the value of harmony memory considering rate, and pitch adjust rate. In this paper, modified harmony search algorithm is proposed in order to derive best harmony. If the optimal solution of a specific problem can not be found for a certain period of time, a part of original harmony memory is updated as the selected suitable harmonies. Experimental results using test function demonstrate that the updated harmony memory can induce the approximation of reliable optimal solution in the short iteration, because of a few change of fitness.