• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.6
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• pp.722-728
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• 2012

Urban sewer systems has a limitation of capacity of rainwater storage and problem of occurrence of untreated sewage, so adopting a storage facility for sewer flooding prevention and urban non-point pollution reduction has a big attention. The Korea Ministry of Environment has recently introduced a new concept of "multi-functional storage facility", which is crucial not only in preventive stormwater management but also in dealing with combined sewer overflow and sanitary sewer discharge, and also has been promoting its adoption. However, reserving a space for a single large-scale storage facility might be difficult especially in urban areas. Thus, decentralized construction of small- and midium-sized storage facilities and its operation have been introduced as an alternative way. In this paper, we propose a model predictive control scheme for an optimized operation of distributed storage facilities and sewer networks. To this aim, we first describe the mathematical model of each component of networks system which enables us to analyze its detailed dynamic behavior. Second, overflow locations and volumes will be predicted based on the developed network model with data on the external inflow occurred at specific locations of the network. MPC scheme based on the introduced particle swarm optimization technique then produces the optimized the gate setting for sewer network flow control, which minimizes sewer flooding and maximizes the potential storage capacity. Finally, the operational efficacy of the proposed control scheme is demonstrated by simulation study with virtual rainstorm event.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.34 no.7
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• pp.679-688
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• 2010

The major objective of the present study is to extend the applications of inverse analysis to more realistic engineering fields with a complex combustion process rather than the traditional simple heat-transfer problems. In order to do this, the unknown initial mass fractions of $CH_4/O_2$ are estimated from the temperature measurement data by inverse analysis in the practical diffusion-controlled turbulent combustion problem. In order to ensure efficient inverse analysis, the repulsive particle swarm optimization (RPSO) method, which belongs to the class of stochastic evolutionary global optimization methods, is implemented as an inverse solver. Based on this study, it is expected that useful information can be obtained when inverse analysis is used in the diagnosis, design, or optimization of real combustion systems involving unknown parameters.

• Proceedings of the Korean Information Science Society Conference
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• 2001.04b
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• pp.244-246
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• 2001

최근 군집화와 분류기법이 데이터 마이닝에 중요한 도구로 많은 응용분야에 사용되고 있다. 따라서 이러한 기법을 이용하는데 있어서 각각의 속성의 중요도가 달라 중요하지 않은 속성에 의해 중요한 속성이 왜곡되거나 때로는 마이닝의 결과가 잘못되는 결과를 얻을 수 있으며, 또한 전체 데이터를 사용할 경우 마이닝 과정을 저하시키는 문제로 속성 가중치과 속성선택에 과한 연구가 중요한 연구의 대상이 되고 있다. 최근 연구되고 있는 알고리즘들은 사용자의 의도와는 상관없이 데이터간의 관계에만 의존하여 가중치를 설정하므로 사용자가 마이닝 결과를 쉽게 이해하고 분석할 수 없는 문제점을 안고 있다. 본 논문에서는 클래스 정보가 있는 데이터뿐 아니라 클래스 정보가 없는 데이터를 분석할 경우 사용자의 의도에 따라 학습할 수 있도록 각 가중치를 부여하는 속성가중치 알고리즘을 제안한다. 또한 사용자가 의도한 정보를 이용하여 속성간의 가장 최적화 된 가중치를 찾아주며, Cramer's $V^2$함수를 적합도 함수로 하는 유전자 알고리즘을 사용한다. 알고리즘의 타당성을 검증하기 위해 전자상거래상의 실험 데이터와 몇 가지 벤치마크 데이터를 이용하여 본 논문의 타당성을 보인다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.4
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• pp.767-778
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• 2003

This paper presents a method for generating optimal fuzzy rules using a genetic algorithm. Fuzzy rules are generated from the training data in the first stage. In this stage, fuzzy c-Means clustering method and cluster validity are used to determine the structure and initial parameters of the fuzzy inference system. A cluster validity is used to determine the number of clusters, which can be the number of fuzzy rules. Once the structure is figured out in the first stage, parameters relating the fuzzy rules are optimized in the second stage. Weights and variance parameters are tuned using genetic algorithms. Variance parameters are also managed with left and right for asymmetrical Gaussian membership function. The method ensures convergence toward a global minimum by using genetic algorithms in weight and variance spaces.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.337-338
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• 2023

컨테이너 해상 유실 사고는 매해 적지 않은 수로 발생하고 있으나 기존에는 사후적 대응, 사전 대응 관점의 대응책들이 대부분이다. 그렇기에 항해 간 컨테이너 유실에 대한 모니터링이 필요한데, 선원들이 항해하는 선박에 적재된 수천 개의 컨테이너를 일일이 들여다보거나 모든 곳에 센서를 부착해 감지하는 것에는 물리적, 경제적 한계가 존재한다. 본 연구는 선박에 적재된 컨테이너들을 3차원 좌표 화하여 선박의 경사시험에서 모티브를 가져와 일정 정도의 기울기를 선박에 적용하였을 때, 기울기 중심을 기준으로 회전운동이 가장 큰 좌표에 해당하는 컨테이너들을 K-평균 군집화를 통해 최적화 위치로 선정하여 센서 위치를 최적화시켜 효율적인 컨테이너 유실 감지를 위한 기반을 마련한다.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.710-710
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• 2012

구형펄스모형(Rectangular Pulse Model)에서 반영하지 못하는 강우의 군집특성을 잘 반영하는 NSRPM(Neyman-Scott Rectangular Pulse Model) 강우생성 모형은 수자원 분야에 널리 쓰이고 있다. 일반적으로 NSRPM의 5개의 매개변수를 추정하는 최적화기법으로 DFP(Davidon-Fletcher-Powell)과 유전자알고리즘(Genetic Algorithm)을 사용하고 있다. 그러나 DFP는 주어진 초기 값에 따라 민감하며 각 반복 단계마다 헤시안행렬(Hessian Matrix)을 계산하여야 하며 추정된 전체의 해가 국지해에 수렴 할 수 있는 단점이 있다. 유전자 알고리즘을 DFP와 다르게 헤시안 행렬을 사용하지 않고 최적화를 할 수 있다는 장점이 있으나 시간이 오래 걸리는 단점이 있다. 이에 본 연구에서는 이러한 단점을 보완, 강화 하기위해서 최적화 기법으로 반복 단계마다 미분계산이 필요하지 않고 빠른 속도로 계산이 가능한 Nelder-Mead 알고리즘 이용하여 NSRPM매개변수를 추정하고 정확도를 비교하였다. 표 1은 각 기법을 이용하여 추정된 매개변수를 이용하여 생성한 강우의 통계특성과 관측된 통계특성의 상대오차를 나타낸 것이다. 괄호 안 숫자는 중첩되지 않는 누적시간을 나타낸다. 상대오차는 다음과 같다(식 1). 분석결과 Nelder-Mead 기법이 1시간의 평균, 공분산과 6시간 분산 등 전체적으로 GA, DFP보다 높은 정확도를 보였다.

• The KIPS Transactions:PartA
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• v.9A no.2
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• pp.197-206
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• 2002

Many researchers have been interested in the optimization of parallel programs through the latency hiding by overlapping the communication with the computation. We ana1yzed overlapping effects in the circular shift communication which is one of the collective communications being frequently used In many data parallel programs. We measured the time which can be possibly overlapped and the time which cannot be overlapped in over all circular shift communication period on an Ethernet switch-based clustered system. The result from each platform nay be used for the input of optimizing compilers. The previous performance models usually have two kinds of drawbacks one is only based on point-to-point communication, so it is not appropriate for analyzing the overall effects of collective communications. The other provides the performance of collective communication, but no overlapping effect. In this paper we extended the previous models and analyzed the experimental results of the extended model.

• The Korean Journal of Applied Statistics
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• v.32 no.3
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• pp.451-462
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• 2019

Document-term frequency matrix is a type of data used in text mining. This matrix is often based on various documents provided by the objects to be analyzed. When analyzing objects using this matrix, researchers generally select only terms that are common in documents belonging to one object as keywords. Keywords are used to analyze the object. However, this method misses the unique information of the individual document as well as causes a problem of removing potential keywords that occur frequently in a specific document. In this study, we define data that can overcome this problem as proximity data. We introduce twelve methods that generate proximity data and cluster the objects through two clustering methods of multidimensional scaling and k-means cluster analysis. Finally, we choose the best method to be optimized for clustering the object.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.5
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• pp.367-379
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• 2022

In this paper, a multilayer radar absorbing structure was designed using the Particle Swarm Optimization (PSO) algorithm, and the characteristics of the multilayer radar absorbing structure were analyzed. It was shown that design values can be derived quickly and accurately by applying PSO to the design of a multilayer radar absorbing structure, and it is also shown that the optimal multilayer radar absorbing structure can be designed especially for an oblique incident. In addition, it was shown that the optimal value that meets the performance requirements can be determined even in a combination of various design parameters. It is presented through a comprehensive flowchart including the equations and detailed descriptions of all variables for each step. From the results of this paper, it is possible to omit complex and many calculations for designing a multilayer radar absorbing structure, and it is possible to use various composite materials. It can be utilized in the design and development of multilayer radar absorbing structures.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.4
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• pp.527-531
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• 2012

In this paper, a novel DPSO-QI (Distributed PSO with quantum-infusion mechanism) algorithm improving one of the fatal defect, the so-called premature convergence, that degrades the performance of the conventional PSO algorithms is proposed. The proposed scheme has the following two distinguished features. First, a concept of neighborhood of each particle is introduced, which divides the whole swarm into several small groups with an appropriate size. Such a strategy restricts the information exchange between particles to be done only in each small group. It thus results in the improvement of particles' diversity and further minimization of a probability of occurring the premature convergence phenomena. Second, a quantum-infusion (QI) mechanism based on the quantum mechanics is introduced to generate a meaningful offspring in each small group. This offspring in our PSO mechanism improves the ability to explore a wider area precisely compared to the conventional one, so that the degree of precision of the algorithm is improved. Finally, some numerical results are compared with those of the conventional researches, which clearly demonstrates the effectiveness and reliability of the proposed DPSO-QI algorithm.