• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.235-238
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• 1996

In this paper, a new optimization method which is a kind of random searching is presented. The proposed method is called RasVal which is an abbreviation of Random Search Method with Variable Seaxch Length and it can search for a global minimum based on the probability density functions of searching, which can be modified using informations on success or failure of the past searching in order to execute intensified and diversified searching. By applying the proposed method to a nonlinear crane control system which can be controlled by the Universal Learning Network with radial basis function(R.B.P.), it has been proved that RasVal is superior in performance to the commonly used back propagation learning algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.9A
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• pp.822-829
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• 2005

In this paper, a processing time and trafnc capacity analysis algorithm for RFID system using LBT-Random Searching scheme is proposed. Service time, carrier sensing time, additional delay time required for contiguous frequency channel occupancy, and additional delay time required for the contiguous using the same frequency channel are considered and the processing delay and frequency channel capacity are analyzed for the steady state operation of the system. The simulation results showing maximum capacity of the system and explaining the accuracy of the algorithm are provided.

• Proceedings of the Korean Geotechical Society Conference
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• 1999.03a
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• pp.331-338
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• 1999

In the present study, a searching technique for critical slip surface in two dimensional slope stability analysis is proposed. The failure surface generation and analysis has been usually limited to simple geometric shapes. However, more random surfaces need to be examined for some particular ground conditions. For this purpose, random searching technique is developed using genetic algorithm. The generalized limit equilibrium method is employed as the method of stability analysis. Using this technique, the factor of safety is compared with the result by using simplified Bishop's method. In addition, the convergent trend of fitness value is analyzed.

• Proceedings of the Acoustical Society of Korea Conference
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• 1995.06a
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• pp.141-145
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• 1995

Code excited linear prediction speech coders exhibit good performance at data rates as low as 4800 bps. The major drawback to CELP type coders is their large computational requirements. In this paper, we propose a new codebook search method that preserves the quality of the CELP vocoder with reduced complexity. The basic idea is to restrict the searching range of the random codebook by using a searching technique of the regular pulse excitation. Applying the proposed method to the CELP vocoder, we can get approximately 48% complexity reduction in the codebook search.

• Communications for Statistical Applications and Methods
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• v.8 no.1
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• pp.73-85
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• 2001

The spatial population existing in a plane ares, such as an animal or aerial population, have certain relationships among regions which are located within a fixed distance from one selected region. We consider with the adaptive searching estimation in spatial sampling for a spatial population. The adaptive searching estimation depends on values of sample points during the survey and on the nature of the surfaces under investigation. In this paper we study the estimation by the adaptive searching in a spatial sampling for the purpose of estimating the area possessing a particular characteristic in a spatial population. From the viewpoint of adaptive searching, we empirically compare systematic sampling with stratified sampling in spatial sampling through the simulation data.

• Journal of information and communication convergence engineering
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• v.11 no.3
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• pp.173-178
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• 2013

To discover objects of interest in unstructured peer-to-peer networks, the peers rely on flooding query messages which create incredible network traffic. This article evaluates the performance of an unstructured Gnutella-like protocol over mobile ad-hoc networks and proposes modifications to improve its performance. This paper offers an enhanced mechanism for an unstructured Gnutella-like network with improved peer features to better meet the mobility requirement of ad-hoc networks. The proposed system introduces a novel caching optimization technique and enhanced ultrapeer selection scheme to make communication more efficient between peers and ultrapeers. The paper also describes an enhanced query mechanism for efficient searching by applying multiple walker random walks with a jump and replication technique. According to the simulation results, the proposed system yields better performance than Gnutella, XL-Gnutella, and random walk in terms of the query success rate, query response time, network load, and overhead.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.111-113
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• 2006

DEAS is an direct searching and optimization method that based on the binary code space. It can be classified as an direct hill climbing searching. However, because of binary code space based searching, the searching in low resolution has random property. As the resolution of code increases during the search, its property of searching changes like that of hill climbing search. This paper propose a method for improving the performance of minimum seeking ability of DEAS with history information. The cost evaluation is increased. However the minimum searching ability of DEAS is improved along the same starting resolution.

• Journal of the Korean Institute of Intelligent Systems
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• v.9 no.6
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• pp.650-656
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• 1999

In this paper, we study on the convergence of the evolution strategies by introducing the Lamarckian evolution and the Baldwin effect, and propose a random local searching and a reinforcement local searching methods. In the random local searching method some neighbors generated randomly from each individual are med without any other information, but in the reinforcement local searching method the previous results of the local search are reflected on the current local search. From the viewpoint of the purpose of the local search it is suitable that we try all the neighbors of the best individual and then search the neighbors of the best one of them repeatedly. Since the reinforcement local searching method based on the Lamarckian evolution and Baldwin effect does not search neighbors randomly, but searches the neighbors in the direction of the better fitness, it has advantages of fast convergence and an improvement on the global searching capability. In other words the performance of the evolution strategies is improved by introducing the learning, reinforcement local search, into the evolution. We study on the learning effect on evolution strategies by applying the proposed method to various function optimization problems.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.284-286
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• 2009

In this paper, we consider a cognitive radio system operating as secondary user. It uses an empty channel that is not currently used by primary users having the license to the channel. In the previous works, secondary user looks for an empty channel by choosing any channel in order or randomly and by sensing the channel to distinguish whether primary users are using. But if primary user is fixed type, we will find an empty channel faster than the mentioned channel selecting methods by using a method considering prior information about cases that primary user used the channel, since it is possible to analogize the channel access possibility of primary user according to regular time and position. Therefore, we propose a channel searching method based on the channel list for the purpose of reducing the channel searching time and improving throughput of secondary users. Firstly, we determine a weighting value of each channel based on the history of channel activities of primary users. This value is added to current channel state buffer and we search an empty channel from channel with smallest value to one with the biggest value. Finally, we compare the performances of the proposed method with those of the sequential channel searching and the random channel searching methods in terms of the average channel searching time and the average number of transmissions of secondary user.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.6
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• pp.1114-1119
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• 2010

This paper is concerned with an numerical analysis of electromagnetic wave propagation from randomly rough surfaces as a desert, sea surface and so on. We propose discrete ray tracing method (DRTM) for analysis of characteristics of wave propagation along one dimensional (1D) and two dimensional (2D) random rough surfaces. The point of the present method is to discretize not only rough surface but also ray tracing. This technique helps saving computer memories and does simplifying ray searching algorithm resulting in saving computation time. Numerical calculations are carried out for 1D and 2D random rough surfaces and electric field distributions are shown to check the effectiveness of the proposed DRTM.