• 정보과학회 논문지
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• 제44권10호
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• pp.1105-1111
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• 2017

영향력 최대화란 소셜 네트워크에서 최대의 영향력을 갖는 k개의 시드(seed) 노드로 이루어진 집합을 선출하는 문제이다. 이 문제를 해결한 기존 방법들이 갖는 가장 큰 문제는 시드 집합을 선출하는데 너무 많은 시간이 소요된다는 점이다. 이러한 성능 문제는 미시적, 거시적 두 가지 측면에서 발생한다. 본 논문은 미시적, 거시적 측면의 성능 문제 동시에 해결하는 효율적인 영향력 최대화 방안을 제안한다. 또한, 양질의 시드 집합을 선출하기 위한 새로운 경로 기반 커뮤니티 탐지 기법을 제안한다. 네 가지 실세계 데이터를 이용한 실험을 통해, 제안하는 방안이 미시적, 거시적 측면의 문제를 모두 해결하는 동시에 양질의 시드 집합을 선출함을 확인하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 심포지엄 논문집 정보 및 제어부문
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• pp.6-8
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• 2005

In this paper, we discuss model identification of nonlinear data using GAs-based Fuzzy Polynomial Neural Networks(GAs-FPNN). Fuzzy Polynomial Neural Networks(FPNN) is proposed model based Group Method Data Handling(GMDH) and Neural Networks(NNs). Each node of FPNN is expressed Fuzzy Polynomial Neuron(FPN). Network structure of nonlinear data is created using Genetic Algorithms(GAs) of optimal search method. Accordingly, GAs-FPNN have more inflexible than the existing models (in)from structure selecting. The proposed model select and identify its for optimal search of Genetic Algorithms that are no. of input variables, input variable numbers and consequence structures. The GAs-FPNN model is select tuning to input variable number, number of input variable and the last part structure through optimal search of Genetic Algorithms. It is shown that nonlinear data model design using Genetic Algorithms based FPNN is more usefulness and effectiveness than the existing models.

• Composites Research
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• 제25권5호
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• pp.147-153
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• 2012

본 논문에서는 복합재 적층판의 고속충격 관통에너지를 예측하는 방법 중 하나인 정적압입 관통 실험을 수행하였다. 정적압입 관통 에너지를 정확히 분석하기 위해서 세 가지 방법을 이용하였다. 첫 번째로 AE 센서 신호 변화를 이용해서 압입 관통 지점을 판단하고 관통 에너지를 구하는 방법, 두 번째는 관통된 시편에 다시 관통실험을 수행하여 두 에너지 차를 이용해서 구하는 방법, 세 번째는 재수행한 관통실험의 하중-변위 그래프에서 최대하중지점을 압입 관통 지점으로 판단하고 에너지를 구하는 방법이다. 위 방법들에 의한 관통에너지 예측 결과를 제시하였고 고속충격 실험 결과와 비교하여 타당성을 검증하였다.

• 한국기계가공학회지
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• 제21권2호
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• pp.137-143
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• 2022

Composite materials, being light-weight and of high mechanical strength, are increasingly used in various industries such as the aerospace, automobile, sporting-goods manufacturing, and ship-building industries. Recently, manufacturing of composite materials using 3D printers has increased. 3D-printed composite materials are made in free-form and adapted for end-use by adjusting the fiber content and orientation. However, research on the machining of 3D printed composite materials is limited. The aim of this study is to develop a machine learning method to select machining conditions for machining of 3D-printed composite materials. The composite material was composed of Onyx and carbon fibers and stacked sequentially. The experiments were performed using the following machining conditions: spindle speed, feed rate, depth of cut, and machining direction. Cutting forces of the different machining conditions were measured by milling the composite materials. PCA, a method of machine learning, was developed to select the machining conditions and will be used in subsequent experiments under various machining conditions.

• 디지털산업정보학회논문지
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• 제19권4호
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• pp.137-146
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• 2023

The dropout of university freshmen is a very important issue in the financial problems of universities. Moreover, the dropout rate is one of the important indicators among the external evaluation items of universities. Therefore, universities need to predict dropout students in advance and apply various dropout prevention programs targeting them. This paper proposes a method to predict such dropout students in advance. This paper is about a method for predicting dropout students. It proposes a method to select dropouts by applying logistic regression using a shift sigmoid classification function using only quantitative data from the first semester of the first year, which most universities have. It is based on logistic regression and can select the number of prediction subjects and prediction accuracy by using the shift sigmoid function as an classification function. As a result of the experiment, when the proposed algorithm was applied, the number of predicted dropout subjects varied from 100% to 20% compared to the actual number of dropout subjects, and it was found to have a prediction accuracy of 75% to 98%.

• 한국건축시공학회지
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• 제8권6호
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• pp.155-160
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• 2008

The BTL project, 4 years since its operation. has benchmarked the PFI Project in Japan and has been introduced. Given the evaluation step to select a preferred bidder, in a technological factor, the basic plans are corrected and complemented, whereas in a price factor, the low price bidding system is being enforced. There is concern that how to select preferred bidders and how to operate project costs during operation and management period may be problematic. Thus, in this study, using the Analytic Hierarchy Process, the method of deciding the priority to select preferred bidders in an early stage of the project and the evaluation model to evaluate the validity of BTL project expenses in process of project enforcement are established. Targeting the group composed of experts who have experiences in the BTL project. Then, the levelling of evaluation factors and grouping have been carried out as following : LCC analysis and disbursement for government including two more detailed factors.

• 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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• 제14권3호
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• pp.326-330
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• 2008

패턴인식 문제에 있어서 다수의 인식기를 사용하는 연구는 주로, 선택된 다수 인식기를 어떻게 결합할 것인가에 중점을 두어 왔으나, 최근에는 인식기 풀로부터 다수 인식기를 선택하려는 연구로 점차 진행되고 있다. 실제로 다수 인식기 시스템의 성능은 인식기들의 결합 방법은 물론, 선택되는 인식기에 의존한다. 따라서, 우수한 성능을 보이는 인식기 집합을 선택하는 것이 필요하며, 다수의 인식기를 선택하는데 있어서 정보이론에 기초한 접근 방법이 시도되었다. 본 논문에서는 인식기 간의 상호정보를 기반으로 인식기를 선택하여 인식기 집합을 구성하고, 다른 인식기 선택 방법들에 의해 구성된 인식기 집합과 그 성능을 비교해 보고자 한다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.520-523
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• 1997

This paper presents FPGA implementation of fuzzy controller using Product-Sum inference method. Product-Sum inference method has much better performance than other inference methods. This fuzzy controller is composed of several digital modules, e.g. fuzzifier, rule base, adder, multiplier, select center and divider, and is operated by error and error variation. We synthesized the fuzzy controller and performed wave simulation using Xilinx VHDL tool(ViewLogic, ViewSim).

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1998년도 추계종합학술대회 논문집
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• pp.747-750
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• 1998

This paper deals with the vehicle arbitration algorithm used in communication system between vehicles and a roadside control unit. To Improve the performance of vehicle arbitration, a random delay counter method is taken into account and modified to select the optimal maximum count value according to the vehicle arrival rate. The suggested algorithm is tested by computer simulation andthe enhanced performance was shown. This method could be applied to various systems which include the communications between transponders and a control unit.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1998년도 추계종합학술대회 논문집
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• pp.139-142
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• 1998

This paper presents a method to determine the rolloff factors of both the digital terrestrial TV modulator and the bandpass filter (BPF) at the digital TV receiver input, using an analytical power spectral density model satisfying given co-channel and adjacent channel protection ratios for the digital terrestrial broadcasting services. Since the proposed method is very simple and effective to use, also can be used regardless of type of systems or modulation techniques, this method is expected to be applied to select some other digital terrestrial broadcasting system specifications.