• 제목/요약/키워드: 퍼지가중치

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Insect Footprint Recognition using Trace Transform and a Fuzzy Method (Trace 변환과 펴지 기법을 이용한 곤충 발자국 인식)

  • Shin, Bok-Suk;Cha, Eui-Young;Woo, Young-Woon
    • Journal of Korea Multimedia Society
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    • v.11 no.11
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    • pp.1615-1623
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    • 2008
  • This paper proposes methods to classify scanned insect footprints. We propose improved SOM and ART2 algorithms for extracting segments, basic areas for feature extraction, and utilize Trace transform and fuzzy weighted mean methods for extracting feature values for classification of the footprints. In the proposed method, regions are extracted by a morphological method in the beginning, and then improved SOM and ART2 algorithms are utilized to extract segments regardless of kinds of insects. Next, A Trace transform method is used to find feature values suitable for various kinds of deformation of insect footprints. In the Trace transform method, Triple features from reconstructed combination of diverse functions, are used to classify the footprints. In general, it is very difficult to decide automatically whether the extracted footprint segment is meaningful for classification or not. So we use a fuzzy weighted mean method for not excluding uncertain footprint segments because the uncertain footprint segments may be possible candidates for classification. We present experimental results of footprint segment extraction and segment classification by the proposed methods.

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Construction of an Exposure Risk Map and Spatial Knowledge Base for Asbestos in Korea (석면 공간지식베이스 구축을 통한 석면 노출위험도 작성)

  • Hwang, Jae-Hong;Lee, Byung-Joo
    • The Journal of Engineering Geology
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    • v.21 no.4
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    • pp.393-402
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    • 2011
  • Asbestos is a toxic material that can lead to lung cancer and other diseases. There is no information regarding areas in Korea that contain asbestos in nature; consequently we need to manage such areas with care. The purpose of this study was to construct a local graded map of asbestos exposure risk based on the natural occurrence of asbestos in rocks. We first developed a means of evaluating the asbestos exposure risk and produced thematic maps based on a field survey. In addition, we constructed a knowledge base for asbestos through analysis, representation and processes about asbestos data and prepare for the development of an evaluation model for asbestos exposure risk. The spatial analysis of asbestos exposure risk is based on a weighted-overlay analysis using expert opinion and the literature, and a fuzzy-overlay analysis using the uncertainty in the data. The map of asbestos exposure risk, compiled according to the weighted and fuzzy operations, is expected to be used to ensure safety and to reduce the risk of exposure to asbestos.

A Study on the Decision Making for Location Selection of Large-scale Discount Stores (대형할인점의 입지선정을 위한 의사결정에 관한 연구)

  • Shim, Jae Heon;Lee, Sung Ho
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.28 no.5D
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    • pp.705-712
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    • 2008
  • The purpose of this study using Fuzzy AHP technique as a decision support system is to propose a structured and available decision making process for location selection of large-scale discount stores. The procedure of this study is divided into two parts to estimate the relative weights of evaluation criteria and analyze the sites of some large discount stores. The results of this study can be summarized as follows; First, compared with the other criteria, the population of primary trade area has the most weight, and moreover, there are the number of rival businesses, dimensions of roads, total population, lot size, purchase cost in order of size. Lastly, the sites of six stores are evaluated relatively, then the optimal location is selected, which proves the applicability for decision making process this study suggests.

Disaster Recovery Priority Decision for Credit Bureau Business Information System: Fuzzy-TOPSIS Approach (신용조회업무 정보시스템의 재난복구 우선순위결정: 퍼지 TOPSIS 접근방법)

  • Yang, Dong-Gu;Kim, Ki-Yoon
    • Management & Information Systems Review
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    • v.35 no.3
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    • pp.173-193
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    • 2016
  • The aim of this paper is to extend the TOPSIS(Technique for Order Preference by Similarity to Ideal Solution) to the fuzzy environment for solving the disaster recovery priority decision problem in credit bureau business information system. In this paper, the rating of each information systems and the weight of each criterion are described by linguistic terms which can be expressed in trapezoidal fuzzy numbers. Then, a vertex method is proposed to calculate the distance between two trapezoidal fuzzy numbers. According to the concept of the TOPSIS, a closeness coefficient is defined to determine the ranking order of all information systems. The combination between the fuzzy set and TOPSIS brings several benefits when compared with other approaches, such that the fuzzy TOPSIS require few fuzzy judgements to parameterization, which contributes to the agility of the decision process, it does not limit the number of alternatives simultaneously evaluated, and it does not cause the ranking reversal problem when a new alternative is included in the evaluation process. This paper is demonstrated with a real case study of a credit rating agency involving 9 evaluation criteria and 9 credit bureau business information systems assessed by 6 evaluators, and provide the systematic disaster recovery framework for BCP(Business Continuity Planning) to practitioner. Finally, this paper show that the procedure of the proposed fuzzy TOPSIS method is well suited as a decision-making tool for the disaster recovery priority decision problem in credit bureau business information system.

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PCA 알고리즘과 개선된 퍼지 신경망을 이용한 여권 인식 및 얼굴 인증

  • Jung Byung-Hee;Park Choong-Shik;Kim Kwang-Baek
    • Proceedings of the Korea Inteligent Information System Society Conference
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    • 2006.06a
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    • pp.336-343
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    • 2006
  • 본 논문에서는 여권 영 상에서 PCA 알고리즘을 이용한 얼굴 인증과 개선된 퍼지 신경망을 이용한 여권 코드 인식 방법을 제안한다. 본 논문에서는 여권영상에 대해 소벨 연산자를 이용하여 에지를 추출하고 에지가 추출된 영상을 수평 스미어링하여 여권코드 영역을 추출한다. 추출된 여권 코드 영역의 기울기를 검사하여 기울기 보정을 하고, 여권 코드 영역을 이진화 한다. 이진화된 여권 코드 영역에 대하여 8방향윤곽선 추적 알고리즘을 적용하여 여권 코드를 추출한다. 추출된 여권 코드는 퍼지 신경망을 개선하여 여권 코드 인식에 적용한다. 개선된 퍼지 신경 망은 입력층과 중간층 사이의 학습 구조로는 FCM 클러스터링 알고리즘을 적용하고 중간층과 출력층 사이의 학습은 일반화된 델타학습 방법을 적용한다. 그리고 학습 성능을 개선하기 위하여 중간층과 출력층의 가중치 조정에 적용되는 학습률을 동적으로 조정하기 위해 퍼지 제어 시스템을 적용한다. 제안된 퍼지 신경망은 목표값과 출력값의 차이에 대한 절대값이 ${\epsilon}$ 보다 적거나 같으면 정확으로 분류하고 크면 부정확으로 분류하여 정확의 총 개수를 퍼지 제어 시스템에 적용하여 학습률과 모멘텀을 동적으로 조정한다. 여권의 주어진 규격에 근거하여 사진 영역을 추출하고 추출된 사진 영역에 대하여 YCbCr와 RGB 정보를 이용하여 얼굴영역을 추출한다. 추출된 얼굴 영역을 PCA 알고리즘과 스냅샷(Snap-Shot) 방법을 적용하여 얼굴 영역의 위조를 판별한다. 제안된 방법의 여권 코드 인식과 얼굴 인증의 성능을 평가하기 위하여 실제 여권 영상에 적용한 결과, 기존의 방법보다 여권 코드 인식과 얼굴 인증에 있어서 효율적인 것을 확인하였다.s, whereas AVs provide much better security.크는 기준년도부터 2031년까지 5년 단위로 계획된 장래도로를 반영하여 구축된다. 교통주제도 및 교통분석용 네트워크는 국가교통DB구축사업을 통해 구축된 자료로서 교통체계효율화법 제9조의4에 따라 공공기관이 교통정책 및 계획수립 등에 활용할 수 있도록 제공하고 있다. 건설교통부의 승인절차를 거쳐 제공하며 활용 후에는 갱신자료 및 활용결과를 통보하는 과정을 거치도록 되어있다. 교통주제도는 국가의 교통정책결정과 관련분야의 기초자료로서 다양하게 활용되고 있으며, 특히 ITS 노드/링크 기본지도로 활용되는 등 교통 분야의 중요한 지리정보로서 구축되고 있다..20{\pm}0.37L$, 72시간에 $1.33{\pm}0.33L$로 유의한 차이를 보였으므로(F=6.153, P=0.004), 술 후 폐환기능 회복에 효과가 있다. 4) 실험군과 대조군의 수술 후 노력성 폐활량은 수술 후 72시간에서 실험군이 $1.90{\pm}0.61L$, 대조군이 $1.51{\pm}0.38L$로 유의한 차이를 보였다(t=2.620, P=0.013). 5) 실험군과 대조군의 수술 후 일초 노력성 호기량은 수술 후 24시간에서 $1.33{\pm}0.56L,\;1.00{\ge}0.28L$로 유의한 차이를 보였고(t=2.530, P=0.017), 술 후 72시간에서 $1.72{\pm}0.65L,\;1.33{\pm}0.3L$로 유의한 차이를 보였다(t=2.540, P=0.016). 6) 대상자의 술 후 폐환기능에 영향을 미치는 요인은 성별로 나타났다. 이에 따

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Localization of a Tracked Robot Based on Fuzzy Fusion of Wheel Odometry and Visual Odometry in Indoor and Outdoor Environments (실내외 환경에서 휠 오도메트리와 비주얼 오도메트리 정보의 퍼지 융합에 기반한 궤도로봇의 위치추정)

  • Ham, Hyeong-Ha;Hong, Sung-Ho;Song, Jae-Bok;Baek, Joo-Hyun;Ryu, Jae-Kwan
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.36 no.6
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    • pp.629-635
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    • 2012
  • Tracked robots usually have poor localization performance because of slippage of their tracks. This study proposes a new localization method for tracked robots that uses fuzzy fusion of stereo-camera-based visual odometry and encoder-based wheel odometry. Visual odometry can be inaccurate when an insufficient number of visual features are available, while the encoder is prone to accumulating errors when large slips occur. To combine these two methods, the weight of each method was controlled by a fuzzy decision depending on the surrounding environment. The experimental results show that the proposed scheme improved the localization performance of a tracked robot.

Fuzzy Neural Networks-Based Call Admission Control Using Possibility Distribution of Handoff Calls Dropping Rate for Wireless Networks (핸드오프 호 손실율 가능성 분포에 의한 무선망의 퍼지 신경망 호 수락제어)

  • Lee, Jin-Yi
    • Journal of Advanced Navigation Technology
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    • v.13 no.6
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    • pp.901-906
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    • 2009
  • This paper proposes a call admission control(CAC) method for wireless networks, which is based on the upper bound of a possibility distribution of handoff calls dropping rates. The possibility distribution is estimated in a fuzzy inference and a learning algorithm in neural network. The learning algorithm is considered for tuning the membership functions(then parts)of fuzzy rules for the inference. The fuzzy inference method is based on a weighted average of fuzzy sets. The proposed method can avoid estimating excessively large handoff calls dropping rates, and makes possibile self-compensation in real time for the case where the estimated values are smaller than real values. So this method makes secure CAC, thereby guaranteeing the allowed CDR. From simulation studies we show that the estimation performance for the upper bound of call dropping rate is good, and then handoff call dropping rates in CAC are able to be sustained below user's desired value.

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Classification of Proximity Relational Using Multiple Fuzzy Alpha Cut(MFAC) (MFAC를 사용한 근접관계의 분류)

  • Ryu, Kyung-Hyun;Chung, Hwan-Mook
    • Journal of the Korean Institute of Intelligent Systems
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    • v.18 no.1
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    • pp.139-144
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    • 2008
  • Generally, real system that is the object of decision-making is very variable and sometimes it lies situations with uncertainty. To solve these problem, it has used statistical methods as significance level, certainty factor, sensitivity analysis and so on. In this paper, we propose a method for fuzzy decision-making based on MFAC(Multiple Fuzzy Alpha Cut) to improve the definiteness of classification results with similarity evaluation. In the proposed method, MFAC is used for extracting multiple a ${\alpha}$-level with proximity degree at proximity relation between relative Hamming distance and max-min method and for minimizing the number of data which are associated with the partition intervals extracted by MFAC. To determine final alternative of decision-making, we compute the weighted value between extracted data by MFAC From the experimental results, we can see the fact that the proposed method is simpler and more definite than classification performance of the conventional methods and determines an alternative efficiently for decision-maker by testing significance of sample data through statistical method.

Implementation of Fuzzy Comprehensive Evaluation System for Multi-level Decision Making (다층 의사결정을 위한 퍼지 포괄 평가 시스템 구축)

  • Park, Yong Kuk;Lee, Min Goo;Jung, Kyung Kwon;Won, Young-Jin
    • Journal of the Institute of Electronics and Information Engineers
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    • v.52 no.7
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    • pp.169-177
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    • 2015
  • This paper described a fuzzy comprehensive evaluation method and implemented assessment system for multi-layer decision making. The proposed method is a assessment before bidding through the key questions using fuzzy comprehensive evaluation method and the entropy weights. The key questions are given by the wider investigation of major sports event organizers. The paper carried out evaluation of single factor and fuzzy comprehensive evaluation from low layer to high layer step by step. In order to verify the effectiveness of proposed method, we built the sports event management service platform (SEMSP) for assessment of applicant city. This method represents a unified one of the quantitative results and the qualitative results based on the judgment of experts.

Noise Removal Algorithm based on Fuzzy Membership Function in AWGN Environments (AWGN 환경에서 퍼지 멤버십 함수에 기반한 잡음 제거 알고리즘)

  • Cheon, Bong-Won;Kim, Nam-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.24 no.12
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    • pp.1625-1631
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    • 2020
  • With the development of IoT technology, various digital equipment is being spread, and accordingly, the importance of data processing is increasing. The importance of data processing is increasing as it greatly affects the reliability of equipment, and various studies are being conducted. In this paper, we propose an algorithm to remove AWGN according to the characteristics of the fuzzy membership function. The proposed algorithm calculates the estimated value according to the correlation between the value of the fuzzy membership function between the input image and the pixel value inside the filtering mask, and obtains the final output by adding or subtracting the output of the spatial weight filter. In order to evaluate the proposed algorithm, it was simulated with existing AWGN removal algorithms, and analyzed using difference image and PSNR comparison. The proposed algorithm minimizes the effect of noise, preserves the important characteristics of the image, and shows the performance of efficiently removing noise.