• 해양환경안전학회지
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• 제21권3호
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• pp.253-258
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• 2015

The purpose of this study is to find suitable probability distribution function of complex distribution data like multimodal. Normal distribution is broadly used to assume probability distribution function. However, complex distribution data like multimodal are very hard to be estimated by using normal distribution function only, and there might be errors when other distribution functions including normal distribution function are used. In this study, we experimented to find fit probability distribution function in multimodal area, by using AIS(Automatic Identification System) observation data gathered in Mokpo port for a year of 2013. By using chi-squared statistic, gaussian mixture model(GMM) is the fittest model rather than other distribution functions, such as extreme value, generalized extreme value, logistic, and normal distribution. GMM was found to the fit model regard to multimodal data of maritime traffic flow distribution. Probability density function for collision probability and traffic flow distribution will be calculated much precisely in the future.

• Journal of Electrical Engineering and Technology
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• 제5권3호
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• pp.423-430
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• 2010

Particle swarm optimization (PSO) algorithm is designed to find a single global optimal point. However, the PSO needs to be modified in order to find multiple optimal points of a multimodal function. These modifications usually divide a swarm of particles into multiple subswarms; in turn, these subswarms try to find their own optimal point, resulting in multiple optimal points. In this work, we present a new PSO algorithm, called coupling PSO to find multiple optimal points of a multimodal function based on coupling particles. In the coupling PSO, each main particle may generate a new particle to form a couple, after which the couple searches its own optimal point using non-stop-moving PSO algorithm. We tested the suggested algorithm and other ones, such as clustering PSO and niche PSO, over three analytic functions. The coupling PSO algorithm was also applied to solve a significant benchmark problem, the TEAM workshop problem 22.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2000년도 춘계학술대회 학술발표 논문집
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• pp.241-244
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• 2000

The optimization method based on an enhanced genetic algorithms is proposed for multimodal function optimization in this paper This method is consisted of two main steps. The first step is global search step using the genetic algorithm(GA) and function assurance criterion(FAC). The belonging of an population to initial solution group is decided according to the FAC. The second step is to decide resemblance between individuals and research optimum solutions by single point method in reconstructive research space. Two numerical examples are also presented in this paper to comparing with conventional methods.

• 제어로봇시스템학회논문지
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• 제6권12호
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• pp.1061-1069
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• 2000

In this paper, a new genetic algorithm is proposed for solving multimodal function optimization problems that are not easily solved by conventional genetic algorithm(GA)s. This algorithm finds one of local optima first and another optima at the next iteration. By repeating this process, we can locate all the local solutions instead of one local solution as in conventional GAs. To avoid converging to the same optimum again, we devise a new genetic operator, called a Mendel operator which simulates the Mendels genetic law. The proposed algorithm remembers the optima obtained so far, compels individuals to move away from them, and finds a new optimum.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2000년도 추계학술대회논문집
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• pp.587-592
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• 2000

The optimization method based on an enhanced genetic algorithms is proposed for multimodal function optimization in this paper. This method is consisted of two main steps. The first step is global search step using the genetic algorithm(GA) and function assurance criterion(FAC). The belonging of an population to initial solution group is decided according to the FAC. The second step is to decide the similarity between individuals, and to research the optimum solutions by simplex method in reconstructive search space. Two numerical examples are also presented in this paper to comparing with conventional methods.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
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• pp.629-633
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• 1998

Proposed here is a parallel genetic algorithm accompanied with intermittent migration among subpopulations. It is intended to maintain diversity in the population for a long period . This method was applied to finding out the global maximum of some multimodal functions for which no other methods seem to be useful . Preferable results and their detailed analysis are also presented.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제8권2호
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• pp.105-110
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• 2008

Human being recognizes emotion fusing information of the other speech signal, expression, gesture and bio-signal. Computer needs technologies that being recognized as human do using combined information. In this paper, we recognized five emotions (normal, happiness, anger, surprise, sadness) through speech signal and facial image, and we propose to method that fusing into emotion for emotion recognition result is applying to multimodal method. Speech signal and facial image does emotion recognition using Principal Component Analysis (PCA) method. And multimodal is fusing into emotion result applying fuzzy membership function. With our experiments, our average emotion recognition rate was 63% by using speech signals, and was 53.4% by using facial images. That is, we know that speech signal offers a better emotion recognition rate than the facial image. We proposed decision fusion method using S-type membership function to heighten the emotion recognition rate. Result of emotion recognition through proposed method, average recognized rate is 70.4%. We could know that decision fusion method offers a better emotion recognition rate than the facial image or speech signal.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2011년도 정기총회 및 추계학술대회 논문집
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• pp.607-613
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• 2011

This paper reviews search methods of multiple reasonable paths to implement multimodal public transportation network of Seoul. Such a large scale multimodal public transportation network as Seoul, the computation time of path finding algorithm is a key and the result of path should reflect route choice behavior of public transportation passengers. Search method of alternative path is divided by removing path method and deviation path method. It analyzes previous researches based on the complexity of algorithm for large-scale network. Applying path finding algorithm in public transportation network, transfer and loop constraints must be included to be able to reflect real behavior. It constructs the generalized cost function based on the smart card data to reflect travel behavior of public transportation. To validate the availability of algorithm, experiments conducted with Seoul metropolitan public multimodal transportation network consisted with 22,109 nodes and 215,859 links by using the deviation path method, suitable for large-scale network.

• 응용통계연구
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• 제7권2호
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• pp.113-130
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• 1994

본 논문에서는 Oh and Berger (1993)의 알고리즘을 확장하여, Oh and Berger의 알고리즘으로 효율적 처리가 어려웠던 복잡한 모양을 가진 다차원 함수의 적분에 보다 더 일반적으로 적용될 수 있는 알고리즘을 제시한다. 예를 들면 다봉함수이면서 동시에 기울어진 모양을 갖는 함수나 모든 극대점들이 다 파악되지 못한 경우 등이다. 제시된 알고리즘은 Oh and Berger의 알고리즘을 단계적으로 수행해 가면서 각 단계마다 새로운 부확률밀도 함수 (component density functin)를 함성 밀도 함수(mixture importance function) 형태인 중요함 수 (importance function에 더해 감으로써 중요함수를 적분 함수에 접근시킨다.

• 동아시아경상학회지
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• 제10권2호
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• pp.55-69
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• 2022

Purpose - This study is a study to investigate the problem of the selection of means of transportation in international logistics by studying the basics of logistics activities, selection factors of transportation methods, and multimodal transportation. Research design, data, methodology - This study is composed of 5 chapters through literature study. Chapter 1 describes the functions and transportation system of international logistics, Chapter 2 selects transportation, Chapter 3 deals with maritime transportation and multimodal transportation, Chapter 4 describes multimodal transportation in terms of customer service, Chapter 5 addresses the implications and conclusions. Results - When looking at the problem of selecting a means of transportation, it is important that the parties involved in the transportation choose which means of transportation for their convenience and profit during the transportation process. Here, there will be factors to consider, including transportation cost, when selecting a means of transportation, and each means of transportation may have characteristics or advantages and disadvantages. Considering all these points, the adoption of multimodal transportation from a customer service point of view may be the answer. Conclusions - This study pays attention to the academic understanding related to the selection of means of transportation and to how usefully this thesis can be used in the selection of transportation related persons, especially shippers, from a practical level.