• Journal of Biomedical Engineering Research
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• v.31 no.1
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• pp.40-49
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• 2010

A rule weight -based fuzzy classification model is proposed to analyze the patterns of admission-discharge of patients as a previous research for differential diagnosis of dyspnea. The proposed model is automatically generated from a labeled data set, supervised learning strategy, using three procedure methodology: i) select fuzzy partition regions from spatial distribution of data; ii) generate fuzzy membership functions from the selected partition regions; and iii) extract a set of candidate rules and resolve a conflict problem among the candidate rules. The effectiveness of the proposed fuzzy classification model was demonstrated by comparing the experimental results for the dyspnea patients' data set with 11 features selected from 55 features by clinicians with those obtained using the conventional classification methods, such as standard fuzzy classifier without rule weights, C4.5, QDA, kNN, and SVMs.

• The Journal of Economics, Marketing and Management
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• v.10 no.5
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• pp.1-6
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• 2022

Purpose: To overcome the question that depends too much on expert's subjective judgment in traditional risk identification, this paper structure the multilevel generalized fuzzy comprehensive evaluation mathematics model of the risk identification of project, to research the risk identification of the project. Research design, data and methodology: This paper constructs the multilevel generalized fuzzy comprehensive evaluation mathematics model. Through iterative algorithm of AHP analysis, make sure the important degree of the sub project in risk analysis, then combine expert's subjective judgment with objective quantitative analysis, and distinguish the risk through identification models. Meanwhile, the concrete method of multilevel generalized fuzzy comprehensive evaluation is probed. Using the index weights to analyse project risks is discussed in detail. Results: The improved fuzzy comprehensive evaluation algorithm is proposed in the paper, at first the method of fuzzy sets core is used to optimize the fuzzy relation matrix. It improves the capability of the algorithm. Then, the method of entropy weight is used to establish weight vectors. This makes the computation process fair and open. And thereby, the uncertainty of the evaluation result brought by the subjectivity can be avoided effectively and the evaluation result becomes more objective and more reasonable. Conclusions: In this paper, we use an improved fuzzy comprehensive evaluation method to evaluate a railroad engineering project risk. It can give a more reliable result for a reference of decision making.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.05a
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• pp.146-149
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• 2000

In this paper, Computer Colour Matching and Kitchen System (CCMKS) is developed on the basis of delphi package and one-chip processor with fuzzy-PID control. CCMKS will be widely used in the colour dyeing industry as an integrated colour matching and dispensing system which have more advantages than the conventional matching or dispensing system, when controlling the real dyeing processes. Delphi is utilized in making database and search/matching routes. The developed matching function reduces the search and matching time to about one third. One-chip processor is designed and manufactured for the distributed control of three-phase induction motors. Fuzzy-PID control is applied to the speed control of three-phase induction motors for a very precise weight of colour at CCMKS. The developed kitchen function decreases the dispensing time to about one twentieth. The experimental results show CCMKS has more excellent search time, more precise weight and much high fidelity than conventional colour matching or dispensing system, in the performance.

• Journal of the Korean Institute of Landscape Architecture
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• v.33 no.4 s.111
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• pp.97-107
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• 2005

This study was carried out to construct accurate and scientific system of assessment indicators in selection of National Trust conservation areas, which was new concept of domestic environment movement and offer the raw data of new analytic method by introducing the fuzzy theory and weight for overcoming the uncertainty of ranking decision. To transform the Likert's scale granted to assessment indicators into the type of triangular fuzzy number(a, b, c), there was conversion to each minimum(a), median(b), and maximum(c) in applying membership function, and in using the center of gravity and eigenvalue, there was to decide the ranking. The rankings of converted values applied a mean importance and weight were confirmed that they were generally changed. Therefore, the ranking decision was better to accomplish objective and rational ranking decision by applying weight that was calculated in grouping of indicator than to judge the singular concept and to be useful in assessment of diverse National Trust site. In the future, because AHP, which was general method of calculating weight, was lacked, there was to understand the critical point to fix a pertinent weight, and to carry out the study applying engineering concept like fuzzy integral using $\lambda-measure$.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1995.10b
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• pp.52-58
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• 1995

A shared-weight neural network that performed classification based on the features extracted with the fuzzy morphological operation is introduced. Learning rules for the structuring elements, degree of membership, and weighting factors are also precisely described. In application to handwritten digit recognition problem, the fuzzy morphological shared-weight neural network produced the results which are comparable to the state-of-art for this problem.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.181-183
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• 1996

Generally, While position type fuzzy controller has good performance in transient period, it has uniform steady state error of response. While velocity type fuzzy controller is capable of reducing steady state error of response, it is hard to develop the performance in transient period. In order to have both good performance in transient period and ability to reduce the steady state error of response, weighting fuzzy controller, which is composed of these two fuzzy controllers, is proposed. For the decision of weight to each fuzzy controller, Weighting fuzzy set is established according to the system state variables and applied to each fuzzy controller. The proposed weighted fuzzy controller has the merits of both position type fuzzy controller and velocity type fuzzy controller simultaneously.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.8
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• pp.715-721
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• 2020

This paper aims to investigate the factors affecting the quality of rural labor in Vietnam, a case study in Thai Nguyen province. For this purpose, we establish an integrated framework of factors affecting the quality of rural labor. We use Fuzzy analytic hierarchy process (Fuzzy-AHP) to assess the weight of the criteria and sub-criteria of rural labor quality. This method introduced by Saaty (1987) is a useful tool to cope with the complexity of decision-making. The Fuzzy-AHP is one of the most common Multi-Criteria Decision-Making instruments for dealing with quantifiable and intangible criteria, which reflect the relative importance of the alternatives based on constructing a pairwise comparison matrix. The results show that the four most weighted factors are institutions, local government policies, technical qualifications, and mentality. In particular, the weight of the institution is the largest (0.2343), meaning that this factor is the most important one affecting the quality of rural labor in Thai Nguyen province. The weight of local government policy is close to that of institution, about 0.2259. The weights of technical qualification and mentality are 0.1238 and 0.1135, respectively. In addition, age and education levels do not significantly affect the rural labor quality of Thai Nguyen province.

• International Journal of Quality Innovation
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• v.7 no.2
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• pp.83-96
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• 2006

In this paper, fuzzy hierarchical analysis (FHA) is used to explore the process by which the criteria weights of the Taiwan National Quality Award (TNQA) are assigned by TNQA committee members. Each member is allowed to employ fuzzy scales in place of exact scales. Each pairwise comparison of criteria is made through a questionnaire from each TNQA committee member. The membership function of trapezoidal fuzzy numbers is introduced to specify TNQA committee members' intentions. After FHA, the reasonable range of each criterion weight of TNQA is determined. The current criteria weights of TNQA are properly verified.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.4 s.310
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• pp.1-8
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• 2006

This paper proposes an improved FCM(Fuzzy C-means) algorithm using intercluster and entropy-based weight in gray image. The fuzzy clustering methods have been extensively used in the image segmentation since it extracts feature information of the region. Most of fuzzy clustering methods have used the FCM algorithm. But, FCM algorithm is still sensitive to noise, as it does not include spatial information. In addition, it can't correctly classify pixels according to the feature-based distributions of clusters. To solve these problems, we applied a weight and intercluster to the traditional FCM algorithm. A weight is obtained from the entropy information based on the cluster's number of neighboring pixels. And a membership for one pixel is given based on the information considering the feature-based intercluster. Experiments has confirmed that the proposed method was more tolerant to noise and superior to existing methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.5C
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• pp.486-492
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• 2003

The vigilance threshold of conventional fuzzy ART algorithm decide whether to permit the mismatch between any input pattern and stored pattern. If the vigilance threshold was large, despite of little difference among input and stored patterns, the input pattern may be classified to new category. On the other hand, if the vigilance threshold was small, the similarity between two patterns may be accepted in spite of lots of difference and the input pattern are classified to category of the stored pattern. Therefore, the vigilance threshold for the image recognition must be experientially set for the good result. Moreover, it may occur in the fuzzy ART algorithm that the information of stored patterns is lost in the weight-adjusting process and the rate of pattern recognition is dropped. In this paper, I proposed the enhanced fuzzy ART algorithm that supports the dynamical setting of the vigilance threshold using the generalized intersection operator of fuzzy logic and the weight value being adaptively set in proportional to the current weight change and the previous weight by reflecting the frequency of the selection of winner node. For the performance evaluation of the proposed method, we applied to the recognition of container identifiers from shipping container images. The experiment showed that the proposed method produced fewer clusters than conventional ART2 and fuzzy ART algorithm. and had tile higher recognition rate.