• Title/Summary/Keyword: Membership Value

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DECISION MAKING USING CUBIC HYPERSOFT TOPSIS METHOD

  • A. BOBIN;P. THANGARAJA;H. PRATHAB;S. THAYALAN
    • Journal of applied mathematics & informatics
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    • v.41 no.5
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    • pp.973-988
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    • 2023
  • In real-life scenarios, we may have to deal with real numbers or numbers in intervals or a combination of both to solve multi-criteria decision-making (MCDM) problems. Also, we may come across a situation where we must combine this interval and actual number membership values into a single real number. The most significant factor in combining these membership values into a single value is by using aggregation operators or scoring algorithms. To overcome such a situation, we suggest the cubic hypersoft set (CHSS) concept as a workaround. Ultimately, this makes it simple for the decision-maker to obtain information without misconceptions. The primary aim of this study is to establish some operational laws for the cubic hypersoft set, present the fundamental properties of aggregation operators and propose an algorithm by using the technique of order of preference by similarity to the ideal solution (TOPSIS) technique based on correlation coefficients to analyze the stress-coping skills of workers.

Speaker-Adaptive Speech Synthesis based on Fuzzy Vector Quantizer Mapping and Neural Networks (퍼지 벡터 양자화기 사상화와 신경망에 의한 화자적응 음성합성)

  • Lee, Jin-Yi;Lee, Gwang-Hyeong
    • The Transactions of the Korea Information Processing Society
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    • v.4 no.1
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    • pp.149-160
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    • 1997
  • This paper is concerned with the problem of speaker-adaptive speech synthes is method using a mapped codebook designed by fuzzy mapping on FLVQ (Fuzzy Learning Vector Quantization). The FLVQ is used to design both input and reference speaker's codebook. This algorithm is incorporated fuzzy membership function into the LVQ(learning vector quantization) networks. Unlike the LVQ algorithm, this algorithm minimizes the network output errors which are the differences of clas s membership target and actual membership values, and results to minimize the distances between training patterns and competing neurons. Speaker Adaptation in speech synthesis is performed as follow;input speaker's codebook is mapped a reference speaker's codebook in fuzzy concepts. The Fuzzy VQ mapping replaces a codevector preserving its fuzzy membership function. The codevector correspondence histogram is obtained by accumulating the vector correspondence along the DTW optimal path. We use the Fuzzy VQ mapping to design a mapped codebook. The mapped codebook is defined as a linear combination of reference speaker's vectors using each fuzzy histogram as a weighting function with membership values. In adaptive-speech synthesis stage, input speech is fuzzy vector-quantized by the mapped codcbook, and then FCM arithmetic is used to synthesize speech adapted to input speaker. The speaker adaption experiments are carried out using speech of males in their thirties as input speaker's speech, and a female in her twenties as reference speaker's speech. Speeches used in experiments are sentences /anyoung hasim nika/ and /good morning/. As a results of experiments, we obtained a synthesized speech adapted to input speaker.

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Enhanced Binarization Method using Fuzzy Membership Function (퍼지 소속 함수를 애용한 개선된 이진화 방법)

  • Kim Kwang Baek;Kim Young Ju
    • Journal of the Korea Society of Computer and Information
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    • v.10 no.1 s.33
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    • pp.67-72
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    • 2005
  • Most of image binarization algorithms analyzes the intensity distribution using the histogram for the determination of threshold value. When the intensity difference between the foreground object and the background is great, the histogram shows the tendency to be bimodal and the selection of the histogram valley as the threshold value shows the good result. On the other side. when the intensity difference is not great and the histogram doesn't show the bimodal property, the histogram analysis doesn't support the selection of the proper threshold value. This Paper Proposed the novel binarization method that applies the fuzzy membership function to each color value on the RGB color model and, by using the operation results, separates the features having the great readability from the background. The proposed method prevents the loss of information incurred by the gray scale conversion by using the RGB color model and extracts effectively the readable features by using the fuzzy inference Compared with the traditional binarization methods, the proposed method is able to remove the majority of noise areas and show the improved results on the image of transport containers , etc.

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A Ranking Method for Type-2 Fuzzy Values (타입-2 퍼지값의 순위결정)

  • Lee, Seungsoo;Lee, Kwang H.
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2002.05a
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    • pp.145-148
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    • 2002
  • Type-1 fuzzy value is used to show the uncertainty in a given value. But there exist many situations that it needs to be extended to type-2 fuzzy value because it is difficult to determine the crisp membership function itself. Intrinsically type-2 fuzzy values are more expressive and powerful than type-1 fuzzy values, but, at the same time, more difficult to be compared or ranked . In this paper, a ranking method for type-2 fuzzy values is proposed. It is based on the satisfaction function which shows the possibility that one type-2 fuzzy value is greater than the other type-2 fuzzy value Some properties of the proposed method are also analyzed .

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Risk Analysis for the Rotorcraft Landing System Using Comparative Models Based on Fuzzy (퍼지 기반 다양한 모델을 이용한 회전익 항공기 착륙장치의 위험 우선순위 평가)

  • Na, Seong Hyeon;Lee, Gwang Eun;Koo, Jeong Mo
    • Journal of the Korean Society of Safety
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    • v.36 no.2
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    • pp.49-57
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    • 2021
  • In the case of military supplies, any potential failure and causes of failures must be considered. This study is aimed at examining the failure modes of a rotorcraft landing system to identify the priority items. Failure mode and effects analysis (FMEA) is applied to the rotorcraft landing system. In general, the FMEA is used to evaluate the reliability in engineering fields. Three elements, specifically, the severity, occurrence, and detectability are used to evaluate the failure modes. The risk priority number (RPN) can be obtained by multiplying the scores or the risk levels pertaining to severity, occurrence, and detectability. In this study, different weights of the three elements are considered for the RPN assessment to implement the FMEA. Furthermore, the FMEA is implemented using a fuzzy rule base, similarity aggregation model (SAM), and grey theory model (GTM) to perform a comparative analysis. The same input data are used for all models to enable a fair comparison. The FMEA is applied to military supplies by considering methodological issues. In general, the fuzzy theory is based on a hypothesis regarding the likelihood of the conversion of the crisp value to the fuzzy input. Fuzzy FMEA is the basic method to obtain the fuzzy RPN. The three elements of the FMEA are used as five linguistic terms. The membership functions as triangular fuzzy sets are the simplest models defined by the three elements. In addition, a fuzzy set is described using a membership function mapping the elements to the intervals 0 and 1. The fuzzy rule base is designed to identify the failure modes according to the expert knowledge. The IF-THEN criterion of the fuzzy rule base is formulated to convert a fuzzy input into a fuzzy output. The total number of rules is 125 in the fuzzy rule base. The SAM expresses the judgment corresponding to the individual experiences of the experts performing FMEA as weights. Implementing the SAM is of significance when operating fuzzy sets regarding the expert opinion and can confirm the concurrence of expert opinion. The GTM can perform defuzzification to obtain a crisp value from a fuzzy membership function and determine the priorities by considering the degree of relation and the form of a matrix and weights for the severity, occurrence, and detectability. The proposed models prioritize the failure modes of the rotorcraft landing system. The conventional FMEA and fuzzy rule base can set the same priorities. SAM and GTM can set different priorities with objectivity through weight setting.

Multi-Mediation Effects of Personal Self-Congruity and Social Self-Congruity to Perceived Value and Brand Attitude on Chinese Airlines Customers

  • WU, Xuan-Wen;KIM, Moon-Hong
    • Journal of Distribution Science
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    • v.18 no.1
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    • pp.35-45
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    • 2020
  • Purpose- This study examines the multi-mediation effect of personal self-congruity and social self-congruity to perceived value and brand attitude on aircraft customers in China. Research design, data and methodology- Survey was conducted on Chinese citizens who had flown via Chinese airlines and lived mainly in the Yangtze River delta. 727 cases were analyzed. SPSS 22.0 and AMOS 24.0 were used to analyze the data. Results - First, perceived economic value has a positive impact on personal self-congruity and social self-congruity but has no effect on brand attitude. Second, perceived functional value has a positive impact on personal self-congruity, social self-congruity, and brand attitude. Third, based on this, perceived economic value is not directly related to brand attitude. However, there is a relationship between perceived functional value and brand attitude, with personal self-congruity and social self-congruity having mediation effects. Conclusions - The Results show that perceived economic and functional value such as competitive airfare, mileage membership, check-in processes, diversified vouchers and coupons, and also basic services such as flight security and flight attendant service having an effect on personal self-congruity. To improve consumer brand attitude, airlines should take into consideration personal self-congruity factors such as their values and lifestyles, and their social self-congruity factors such as their social status and social security.

Mapping of Inundation Vulnerability Using Geomorphic Characteristics of Flood-damaged Farmlands - A Case Study of Jinju City - (침수피해 정보를 이용한 농경지의 지형학적 침수취약지도 작성 - 진주시를 사례로 -)

  • Kim, Soo-Jin;Suh, Kyo;Kim, Sang-Min;Lee, Kyung-Do;Jang, Min-Won
    • Journal of Korean Society of Rural Planning
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    • v.19 no.3
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    • pp.51-59
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    • 2013
  • The objective of this study was to make a map of farmland vulnerability to flood inundation based on morphologic characteristics from the flood-damaged areas. Vulnerability mapping based on the records of flood damages has been conducted in four successive steps; data preparation and preprocessing, identification of morphologic criteria, calculation of inundation vulnerability index using a fuzzy membership function, and evaluation of inundation vulnerability. At the first step, three primary digital data at 30-m resolution were produced as follows: digital elevation model, hill slopes map, and distance from water body map. Secondly zonal statistics were conducted from such three raster data to identify geomorphic features in common. Thirdly inundation vulnerability index was defined as the value of 0 to 1 by applying a fuzzy linear membership function to the accumulation of raster data reclassified as 1 for cells satisfying each geomorphic condition. Lastly inundation vulnerability was suggested to be divided into five stages by 0.25 interval i.e. extremely vulnerable, highly vulnerable, normally vulnerable, less vulnerable, and resilient. For a case study of the Jinju, farmlands of $138.6km^2$, about 18% of the whole area of Jinju, were classified as vulnerable to inundation, and about $6.6km^2$ of farmlands with elevation of below 19 m at sea water level, slope of below 3.5 degrees, and within 115 m distance from water body were exposed to extremely vulnerable to inundation. Comparatively Geumsan-myeon and Sabong-myeon were revealed as the most vulnerable to farmland inundation in the Jinju.

An adaptive Fuzzy Binarization (적응 퍼지 이진화)

  • Jeon, Wang-Su;Rhee, Sang-Yong
    • Journal of the Korean Institute of Intelligent Systems
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    • v.26 no.6
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    • pp.485-492
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    • 2016
  • A role of the binarization is very important in separating the foreground and the background in the field of the computer vision. In this study, an adaptive fuzzy binarization is proposed. An ${\alpha}$-cut control ratio is obtained by the distribution of grey level of pixels in a sliding window, and binarization is performed using the value. To obtain the ${\alpha}$-cut, existing thresholding methods which execution speed is fast are used. The threshold values are set as the center of each membership function and the fuzzy intervals of the functions are specified with the distribution of grey level of the pixel. Then ${\alpha}$-control ratio is calculated using the specified function and binarization is performed according to the membership degree of the pixels. The experimental results show the proposed method can segment the foreground and the background well than existing binarization methods and decrease loss of the foreground.

A Study on the Performance of Fuzzy Inference Engine (퍼지 추론부의 성능 향상에 관한 연구)

  • 우찬일;신인철;유종상
    • Proceedings of the Korea Society for Industrial Systems Conference
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    • 1997.11a
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    • pp.105-116
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    • 1997
  • The fuzzy logic controller was used effectively for the controlling of unmeasured parameter and inaccurate mathematical modeling was designed. In this paper, we proposed that the method of reducing the vibration at the target point on calculating the membership degree about input value without a look-up table was proposed. And its effectiveness in the inverted pendulum was acquired.

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Consideration on the Fuzzy Chaos Dimension for Speech Recognition (음성인식을 위한 퍼지 카오스 차원의 고찰)

  • Yoo, B.W.;Kim, S.K.;Park, H.S.;Kim, C.S.
    • Speech Sciences
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    • v.4 no.2
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    • pp.25-39
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    • 1998
  • This paper deals with fuzzy correlation dimension for an appropriate speech recognition. The proposed fuzzy correlation dimension has absorbed time variation value of strange attractor as utilizing fuzzy membership function at calculation of integral correlation when the results of proposed dimension are applied to speech recognition fuzzed correlation dimension is superior to speech recognition, and correlation dimension is superior to speaker discrimination.

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