• Smart Structures and Systems
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• 제26권3호
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• pp.345-360
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• 2020

Modern swarm intelligence heuristic search methods are widely applied in the field of structural health monitoring due to their advantages of excellent global search capacity, loose requirement of initial guess and ease of computational implementation etc. To this end, a hybrid strategy is proposed based on butterfly optimization algorithm (BOA) and differential evolution (DE) with purpose of effective combination of their merits. In the proposed identification strategy, two improvements including mutation and crossover operations of DE, and dynamic adaptive operators are introduced into original BOA to reduce the risk to be trapped in local optimum and increase global search capability. The performance of the proposed algorithm, hybrid butterfly optimization and differential evolution algorithm (HBODEA) is evaluated by two numerical examples of a simply supported beam and a 37-bar truss structure, as well as an experimental test of 8-story shear-type steel frame structure in the laboratory. Compared with BOA and DE, the numerical and experimental results show that the proposed HBODEA is more robust to detect the reduction of stiffness with limited sensors and contaminated measurements. In addition, the effect of search space, two dynamic operators, population size on identification accuracy and efficiency of the proposed identification strategy are further investigated.

• Journal of Astronomy and Space Sciences
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• 제20권1호
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• pp.29-42
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• 2003

2002년 11월에 발사된 과학로켓 KSR-111에 자세제어를 위한 정보 획득용 3축 Fluxgate 자력계 (AIM: Attitude Information Magnetometer)와 지구 자기장 섭동 측정용 Search-Coil 자력계(SIM: Scientific Investigation Magnetometer)가 탑재되었다. SIM은 지구 자기장 중 약 10～1,000Ha주파수 대의 섭동 현상을 관측한다. AIM을 통해 측정한 지구 자기장의 DC 벡터 성분을 지구 자기장의 기준 모델인 IGRF(International Geomagnetic Reference Field)와 비교하여 로켓의 위치와 비행 상태를 파악하는 프로그램 1과 KSR-Ⅲ에서 측정된 실제 데이터를 이용해 시간에 따른 회전 각의 변화를 알아보는 프로그램 2를 개발하였다. 알고리즘 개발시 자세제어의 요소로서 데이터 처리 속도, 로켓의 비행역학 등을 고려하였고, 이로 인한 오차를 감안하기 위해 최소자승법을 사용하였다. 프로그램 2를 실행하여 얻은 값으로(항우연 자료 비교분석한 결과 내용), 자력계를 로켓의 자세 제 어용으로는 부적합하나 붐(boom)이 장착된 로켓에 탑재할 경우 지구 상충의 자기장을 측정하여 분석할 수 있다. 또한 발사 전 로켓 몸체와 마운트의 자기장을 측정하여 로켓의 자기장'분포를 미리 모델링화 할 경우 자료 처리가 훨씬 용이하다.

• 대한교통학회지
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• 제14권1호
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• pp.51-67
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• 1996

The optimal path-finding problem becomes complicated when multiple variables are simultaneously considered such as physical route length, degree of congestion, traffic capacity of intersections, number of intersections and lanes, and existence of free ways. Therefore, many researchers in various fields (management science, computer science, applied mathematics, production planning, satellite launching) attempted to solve the problem by ignoring many variables for problem simplification, by developing intelligent algorithms, or by developing high-speed hardware. In this research, an integration of expert system technique and case-based reasoning in high level with a conventional algorithms in lower level was attempted to develop an optimal path-finding system. Early application of experienced driver's knowledge and case data accumulated in case base drastically reduces number of possible combinations of optimal paths by generating promising alternatives and by eliminating non-profitable alternatives. Then, employment of a conventional optimization algorithm provides faster search mechanisms than other methods such as bidirectional algorithm and $A^*$ algorithm. The conclusion obtained from repeated laboratory experiments with real traffic data in Seoul metropolitan area shows that the integrated approach to finding optimal paths with consideration of various real world constraints provides reasonable solution in a faster way than others.

• International Journal of Computer Science & Network Security
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• 제21권1호
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• pp.40-48
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• 2021

Content-Based Image Retrieval (CBIR) system plays a vital role to retrieve the relevant images as per the user perception from the huge database is a challenging task. Images are represented is to employ a combination of low-level features as per their visual content to form a feature vector. To reduce the search time of a large database while retrieving images, a novel image retrieval technique based on feature dimensionality reduction is being proposed with the exploit of metaheuristic optimization techniques based on Genetic Algorithm (GA), Extended Binary Cuckoo Search (EBCS) and Whale Optimization Algorithm (WOA). Each image in the database is indexed using a feature vector comprising of fuzzified based color histogram descriptor for color and Median binary pattern were derived in the color space from HSI for texture feature variants respectively. Finally, results are being compared in terms of Precision, Recall, F-measure, Accuracy, and error rate with benchmark classification algorithms (Linear discriminant analysis, CatBoost, Extra Trees, Random Forest, Naive Bayes, light gradient boosting, Extreme gradient boosting, k-NN, and Ridge) to validate the efficiency of the proposed approach. Finally, a ranking of the techniques using TOPSIS has been considered choosing the best feature selection technique based on different model parameters.

• 전기학회논문지
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• 제59권2호
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• pp.436-444
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• 2010

In this study, we introduce and discuss a concept of a granular-oriented radial basis function neural networks (GRBF NNs). In contrast to the typical architectures encountered in radial basis function neural networks(RBF NNs), our main objective is to develop a design strategy of GRBF NNs as follows : (a) The architecture of the network is fully reflective of the structure encountered in the training data which are granulated with the aid of clustering techniques. More specifically, the output space is granulated with use of K-Means clustering while the information granules in the multidimensional input space are formed by using a so-called context-based Fuzzy C-Means which takes into account the structure being already formed in the output space, (b) The innovative development facet of the network involves a dynamic reduction of dimensionality of the input space in which the information granules are formed in the subspace of the overall input space which is formed by selecting a suitable subset of input variables so that the this subspace retains the structure of the entire space. As this search is of combinatorial character, we use the technique of genetic optimization to determine the optimal input subspaces. A series of numeric studies exploiting some nonlinear process data and a dataset coming from the machine learning repository provide a detailed insight into the nature of the algorithm and its parameters as well as offer some comparative analysis.

• 대한전자공학회논문지TC
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• 제43권8호
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• pp.59-68
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• 2006

채널 부호의 균일 오율에 대한 연구는 부가성백색가우시안 채널에 대해 국한되어 연구되어 왔으며, 기하학적 균일성으로 불려왔다. 본 논문에서는 전송 채널과 수신기를 완전히 묘사해주는 확률밀도함수를 직접 다루어 균일 오율 특성을 다중 송수신안테나가 사용되는 시공간 부호로 확장한다. 또한 빠른 페이딩 채널에서 곱거리 스펙트럼를 고려한 기하학적 균일 시공간 부호 설계 과정을 보여준다. 균일 오율 특성으로 부호 검색의 복잡도가 현격히 감소하고, 이런 복잡도 감소는 높은 상태 수를 갖는 시공간 격사상 부호에 대해서도 최적의 부호 검색을 가능하게 한다. 모의 실험을 통해 새로 설계된 부호가 다른 알려진 부호들에 비해 빠른 페이딩 채널에서 더 좋은 성능을 가지는 것을 확인한다.

• International Journal of Aeronautical and Space Sciences
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• 제17권3호
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• pp.285-295
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• 2016

A contact strip shape of a high speed train pantograph system was optimized with CFD to increase the aerodynamic performance and stability of contact force, and the results were validated by a wind tunnel test. For design of the optimal contact strip shape, a Kriging model and genetic algorithm were used to ensure the global search of the optimal point and reduce the computational cost. To enhance the performance and robustness of the contact strip for high speed pantograph, the drag coefficient and the fluctuation of the lift coefficient along the angle of attack were selected as design objectives. Aerodynamic forces were measured by a load cell and HWA (Hot Wire Anemometer) was used to measure the Strouhal number of wake flow. PIV (Particle Image Velocimetry) was adopted to visualize the flow fields. The optimized contact strip shape was shown a lower drag with smaller fluctuation of vertical lift force than the general shaped contact strip. And the acoustic noise source strength of the optimized contact strip was also reduced. Finally, the reduction amount of drag and noise was assessed when the optimized contact strip was applied to three dimensional pantograph system.

• 한국항공우주학회지
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• 제37권3호
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• pp.248-254
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• 2009

유전자 알고리즘은 공기역학적 최적 형상 설계를 위해 매우 유용한 도구임에도 불구하고 인구수 기반의 탐색 알고리즘이 내포하고 있는 과도한 계산 시간으로 말미암아 제한적으로 적용된다. 본 연구에서는 과도한 계산 시간을 줄이고 정확한 최적해를 유도하기 위해 근사모델인 역전파 신경망과 전역적 최적화 기법인 실수기반 적응영역 유전자 알고리즘을 결합한 하이브리드 기법을 제안한다. 그 결과 하이브리드 기법이 에어포일의 항력 및 최적화 계산 시간 측면에서 일반적인 유전자 알고리즘 대비 14%, 33% 향상된 결과를 나타내었다.

• 전자공학회논문지S
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• 제34S권5호
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• pp.52-65
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• 1997

For the degradation of severe noise and ill-conditioned blur the optimization function has the solution spaces which have many local optima around global solution. General restoration methods such as inverse filtering or gradient methods are mainly dependent on the properties of degradation model and tend to be isolated into a local optima because their convergences are determined in the convex space. Hence we introduce genetic algorithm as a searching method which will search solutions beyond the convex spaces including local solutins. In this paper we introudce improved evaluation square error) and fitness value for gray scaled images. Finally we also proposed the local fine tunign of window size and visit number for delicate searching mechanism in the vicinity of th global solution. Through the experiental results we verified the effectiveness of the proposed genetic operators and evaluation function on noise reduction over the conventional ones, as well as the improved performance of local fine tuning.

• 한국데이터정보과학회:학술대회논문집
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• 한국데이터정보과학회 2005년도 춘계학술대회
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• pp.164-173
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• 2005

Data mining is the method to find useful information for large amounts of data in database. It is used to find hidden knowledge by massive data, unexpectedly pattern, relation to new rule. The methods of data mining are decision tree, association rules, clustering, neural network and so on. The decision tree approach is most useful in classification problems and to divide the search space into rectangular regions. Decision tree algorithms are used extensively for data mining in many domains such as retail target marketing, fraud detection, data reduction and variable screening, category merging, etc. We analyze waste database united with local information using decision tree techniques for environmental information. We can use these decision tree outputs for environmental preservation and improvement.