• 자원환경지질
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• 제17권3호
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• pp.163-169
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• 1984

암석의 대표적 열원치(熱源値)를 사용하여 지각 열류량(熱流量)의 반전(反轉)을 연구하였으며 2-D 모델은 아주 얇은 정방형판(正方形板)이 고려되었다. 포텐샬 이론을 기초로 하여 지각 열류량과 열원 사이의 새로운 관계를 도출하였으며 두가지 경우의 계산결과가 도시되어 있다. Random search 방법과 ridge regression방법이 비교되었으며 지각열류량의 반전(反轉) 연구에서는 random search 방법의 중요성이 발견되었다.

• 전기학회논문지P
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• 제59권1호
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• pp.47-52
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• 2010

The low power of ultra-wideband (UWB) signal makes the acquisition of UWB signal be a more challenging task. In this paper, we propose the method of high order template signal technique that reduces the synchronization time. Experimental results are presented to show the improvements of performance in the mean acquisition time (MAT) and the probability of detection. The performance compared with the serial search, the truly random search and the random permutation search. It is shown that over typical UWB multipath channels, a random permutation search scheme may yield lower MAT than serial search.

• 전기학회논문지P
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• 제66권3호
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• pp.123-128
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• 2017

Electric utilities has been considered the necessity to introduce AM(asset management) of electric power facilities in order to reduce maintenance cost of existing facilities and to maximize profit. In order to make decisions in terms of repairs and replacements for power transformers, not only measuring by counting parts and labor costs, but comprehensive comparison including reliability and cost is needed. Therefore, this study is modeling input cost for power transformer during its entire life and also the life cycle cost (LCC) technique is applied. In particular, this paper presents an application of heuristic harmony search(HS) optimization algorithm to the convergence and the validity of economic life assessment of power transformer from LCC technique. This recently developed HS algorithm is conceptualized using the musical process of searching for a perfect state of harmony. It uses a stochastic random search instead of a gradient search so that derivative information is unnecessary. The effectiveness of the proposed identification method has been demonstrated through an economic life assessment simulation of power transformer using HS optimization algorithm.

• International Journal of Aeronautical and Space Sciences
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• 제5권2호
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• pp.1-8
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• 2004

Real-Time Kinematic GPS positioning is widely used for many applications.Resolving ambiguities is the key to precise positioning. Integer ambiguity resolution isthe process of resolving the unknown cycle ambiguities of double difference carrierphase data as integers. Two important issues of resolving are efficiency andreliability. In the conventional search techniques, we generally used chi-squarerandom variables for decision variables. Mathematically, a chi-square random variableis the sum of mutually independent, squared zero-mean unit-variance normal(Gaussian) random variables. With this base knowledge, we can separate decisionvariables to several normal random variables. We showed it with related equationsand conceptual diagrams. With this separation, we can improve the computationalefficiency of the process without losing the needed performance. If we averageseparated normal random variables sequentially, averaged values are also normalrandom variables. So we can use them as decision variables, which prevent from asudden increase of some decision variable. With the method using averaged decisionvalues, we can get the solution more quicklv and more reliably.To verify the performance of our proposed algorithm, we conducted simulations.We used some visual diagrams that are useful for intuitional approach. We analyzedthe performance of the proposed algorithm and compared it to the conventionalmethods.

• 한국컴퓨터정보학회논문지
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• 제22권12호
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• pp.117-123
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• 2017

The personalized search algorithm is a search system that analyzes the user's IP, cookies, log data, and search history to recommend the desired information. As a result, users are isolated in the information frame recommended by the algorithm. This is called 'Filter bubble' phenomenon. Most of the personalized data can be deleted or changed by the user, but data stored in the service provider's server is difficult to access. This study suggests a way to neutralize personalization by keeping on sending random query words. This is to confuse the data accumulated in the server while performing search activities with words that are not related to the user. We have analyzed the rank change of the URL while conducting the search activity with 500 random query words once using the personalized account as the experimental group. To prove the effect, we set up a new account and set it as a control. We then searched the same set of queries with these two accounts, stored the URL data, and scored the rank variation. The URLs ranked on the upper page are weighted more than the lower-ranked URLs. At the beginning of the experiment, the difference between the scores of the two accounts was insignificant. As experiments continue, the number of random query words accumulated in the server increases and results show meaningful difference.

• International Journal of Naval Architecture and Ocean Engineering
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• 제8권6호
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• pp.602-614
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• 2016

It is necessary to develop an efficient optimization technique to perform optimum designs which have given design spaces, discrete design values and several design goals. As optimization techniques, direct search method and stochastic search method are widely used in designing of ship structures. The merit of the direct search method is to search the optimum points rapidly by considering the search direction, step size and convergence limit. And the merit of the stochastic search method is to obtain the global optimum points well by spreading points randomly entire the design spaces. In this paper, Pareto Strategy (PS) multi-objective function method is developed by considering the search direction based on Pareto optimal points, the step size, the convergence limit and the random number generation. The success points between just before and current Pareto optimal points are considered. PS method can also apply to the single objective function problems, and can consider the discrete design variables such as plate thickness, longitudinal space, web height and web space. The optimum design results are compared with existing Random Search (RS) multi-objective function method and Evolutionary Strategy (ES) multi-objective function method by performing the optimum designs of double bottom structure and double hull tanker which have discrete design values. Its superiority and effectiveness are shown by comparing the optimum results with those of RS method and ES method.

• 대한조선학회논문집
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• 제42권2호
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• pp.175-182
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• 2005

It is necessary to develop an efficient optimization technique to optimize the engineering structures which have given design spaces, discrete design values and several design goals. As optimization techniques, direct search method and stochastic search method are widely used in designing of engineering structures. The merit of the direct search method is to search the optimum points rapidly by considering the search direction, step size and convergence limit. And the merit of the stochastic search method is to obtain the global optimum points by spreading point randomly entire the design spaces. In this paper, a Pareto optimal based multi-objective function method (PMOFM) is developed by considering the search direction based on Pareto optimal points, step size, convergence limit and random search generation . The PMOFM can also apply to the single objective function problems, and can consider the discrete design variables such as discrete plate thickness and discrete stiffener spaces. The design results are compared with existing Evolutionary Strategies (ES) method by performing the design of double bottom structures which have discrete plate thickness and discrete stiffener spaces.

• 대한건축학회논문집:구조계
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• 제33권12호
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• pp.53-62
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• 2017

Many gradient-based mathematical methods have been developed and are in use for structural size optimization problems, in which the cross-sectional areas or sizing variables are usually assumed to be continuous. In most practical structural engineering design problems, however, the design variables are discrete. The main objective of this paper is to propose an efficient optimization method for structures with discrete-sized variables based on the harmony search (HS) meta-heuristic algorithm that is derived using penalty function. The recently developed HS algorithm was conceptualized using the musical process of searching for a perfect state of harmony. It uses a stochastic random search instead of a gradient search so that derivative information is unnecessary. In this paper, a discrete search strategy using the HS algorithm with a static penalty function is presented in detail and its applicability using several standard truss examples is discussed. The numerical results reveal that the HS algorithm with the static penalty function proposed in this study is a powerful search and design optimization technique for structures with discrete-sized members.

• 지구물리와물리탐사
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• 제23권3호
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• pp.157-167
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• 2020

최근 인공지능 기술의 발전과 함께 물리탐사의 다양한 분야에서도 인공지능의 핵심 기술인 머신러닝의 활용도가 증가하고 있다. 또한 머신러닝 및 딥러닝을 활용한 연구는 이미지, 비디오, 음성, 자연어 등 다양한 태스크의 추론 정확도를 높이기 위해 복잡한 알고리즘들이 개발되고 있고, 더 나아가 자료의 특성, 알고리즘 구조 및 하이퍼 파라미터의 최적화를 위한 자동 머신러닝(AutoML) 분야로 그 폭을 넓혀가고 있다. 본 연구에서는 AutoML 분야 중에서도 하이퍼 파라미터(hyperparameter) 자동 탐색을 위한 베이지안 최적화 기술에 중점을 두었으며, 본 기술을 물리탐사 분야에서도 암상 분류(facies classification) 문제에 적용했다. Vincent field의 현장 물리검층 및 탄성파 자료를 이용하여 암상 및 공극유체를 분류하는 지도학습 기반 모델에 적용하였고, 랜덤 탐색 기법의 결과와 비교하여 베이지안 최적화 기반 예측 프레임워크의 효율성을 검증하였다.

• 대한조선학회논문집
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• 제42권3호
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• pp.284-289
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• 2005

A structural design system is developed for the optimum design of double hull tankers based on the multi-objective function method. As a multi-objective function method, Pareto optimal based random search method is adopted to find the minimum structural weight and fabrication cost. The fabrication cost model is developed by considering the welding technique, welding poses and assembly stages to manage the fabrication man-hour and process. In this study, a new structural design is investigated due to the rapidly increased material cost. Several optimum structural designs on the basis of high material cost are carried out based on the Pareto optimal set obtained by the random search method. The design results are compared with existing ship, which is designed under low material cost.