• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.447-452
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• 1998

A fault is considered as a variation of physical parameters; therefore the design of fault detection and identification(FDI) can be reduced to the parameter identification of a non linear system and to the association of the set of the estimated parameters with the mode of faults. ANFIS(Adaptive Neuro-Fuzzy Inference System) which contains multiple linear models as consequent part is used to model non linear systems. In this paper, we proposes an FDI system for non linear systems using ANFIS. The proposed diagnositc system consists of two ANFISs which operate in two different modes (parallel-and series-parallel mode). It generates the parameter residuals associated with each modes of faults which can be further processed by additional RBF (Radial Basis function) network to identify the faults. The proposed FDI scheme has been tested by simultation on a two-tank system

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.329-330
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• 2007

본 논문에서는 particle swarm optimization(PSO)를 통한 비선형시스템의 퍼지집합 퍼지모델의 최적화 방법을 제안한다. 퍼지 모델링에서 전반부 동정, 즉 구조 동정 및 파라미터 동정은 비선형 시스템을 표현하는데 있어서 매우 중요하다. 퍼지모델의 전반부 동정에 있어 최적화 과정이 필요하며 유전자 알고리즘(Genetic Algorithm; GA)을 이용하여 퍼지모델을 최적화한 연구가 많이 있다. 본 연구는 파라미터 동정 시 최근 여러 가지 어려운 최적화 문제를 수행함에 있어서 성능의 우수성이 증명된 PSO를 이용하여 퍼지집합 퍼지모델의 전반부 파라미터를 동정하였다. 구조동정은 단순 유전자 알고리즘(Simple Genetic Algorithm; SGA)을 이용하여 동정하였으며 파라미터 동정시 실수 코딩유전자 알고리즘(Real Coded Genetic Algorithm; RCGA)와 PSO를 각각 파라미터 동정에 이용하여 성능을 비교하였다.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1547-1548
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• 2008

본 논문에서는 유동적 비정상 시계열의 패턴과 규칙성을 잘 반영할 수 있는 최적의 차분 간격 후보군을 이용한 TS 퍼지 모델로 다중 퍼지 모델을 구현하였고, 각각의 모델들의 예측 특성을 반영하기 위하여 러프집합을 이용한 모델선택법을 제안하였다. 또한 TS퍼지 모델의 파라미터 식별에는 적절한 오차보정 메커니즘을 추가하여 더욱 예측 성능을 향상 시켰다.

• The Transactions of the Korea Information Processing Society
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• v.6 no.8
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• pp.2188-2195
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• 1999

This paper proposes a new call admission control scheme utilizing an inverse fuzzy vector quantizer(IFVQ) and neuralnet, which combines benefits of IFVQ and flexibilities of FCM(Fuzzy-C-Means) arithmetics, to decide whether a requested call not to be trained in learning phase to be connected or not. The system generates the estimated traffic pattern for the cell stream of a new call, using feasible/infeasible patterns in codebook, fuzzy membership values that represent the degree to which each pattern of codebook matches input pattern, and FCM arithmetics. The input to the NN is the vector consisted of traffic parameters which are the means and variances of the number of cells arriving in decision as to whether to accept or reject a new call depends on whether the NN is used for decision threshold(+0.5). This method is a new technique for call admission control using the membership values as traffic parameter which declared to CAC at the call set up stage, and this is valid for a very general traffic model in which the calls of a stream can belong to an unlimited number of traffic classes. Through the simulations, it is founded the performance of the suggested method outperforms compared to the conventional NN method.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.29 no.1
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• pp.77-83
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• 2005

In collision avoidance problem of a ship, collision risk model is usually set up using the interview results fron experts who sit on a simulator by varying parameters, in which DCPA and TCPA are commonly used. This method, however, has the weakness in that not only it is expensive but also it shows different results depending on the inerviewees and other navigational parameters. In this study, a fuzzy inference system is designed based on own ship's maneuverability verified fron simulation instead of interviewing navigators. The time and distance corresponding to the collision risk value on which avoidance maneuver should be started are set to the minimum marginal time at which own ship starts maneuvering and the minimum marginal distance suggested by marine traffic rules respectively. This system can be recorfigured as a nonlinearity-strengthened one by increasing the number of fuzzy membership functions.

• Journal of Environmental Impact Assessment
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• v.8 no.3
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• pp.1-11
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• 1999

This study was carried out to evaluate urban environmental structure in Taegu metropolitan region(TMR) with factor analysis, fuzzy set theory, geostatistic and geographic information system(GIS). The factor analysis could choose the representative one out of multiple variables and simplify the evaluation of the urban environmental structure. The fuzzy approach is an attempt to model an aspect of human thinking previously neglected; it starts from the premise that humans don't represent classes of objects as fully disjoint but rather as sets where transitions from membership to non-membership is gradual. The Geographic Information System(GIS) could connect attributes of factor scores derived from factor analysis to digital map by a method so called 'Spatial join'. The results obtained were as follows: Urbanization appearance was concentrated in the large cities, and this appearance was partial extremely, therefore, there has been a structural gap between urban area and agricultural area which was unified into the urban area. All inclinations didn't become worse after sudden urbanization. For example, suburban agriculture was developed as a large scale in the region near the large cities. Then it encouraged farmers in changing their old cultivating methods to the latest ones. But many districts in urban fringe had symptom of urbanization, the districts which were located between large cities have been developed gradually because of urban sprawl, and played a role in connecting each city. Therefore, due to the urbanization, forestry area and agricultural land, well conserved in the agricultural town, could be easily destroyed. In a different way with the urbanization of the Seoul metropolitan region, that of TMR was centralized upon the center of each city, and it was also very partial. But, because so many regions have the potentiality of urbanization, hereafter, the urbanization process in each region is likely to be different multifariously according to the urban management methods.

• Journal of the Korea Society of Computer and Information
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• v.14 no.9
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• pp.167-177
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• 2009

As the service quality has been reconsidered in public sector as well as private enterprises, the need for public sectors to adopt principle and practices of private sectors is concerned with customer-focused approach, the different business culture of public service organizations makes it difficult to improve service qualify. Also, Since concept of service contains intangibility, heterogeneity, Simultaneousness and perishability, it makes peoples more difficult to measure service quality. Therefore, this study proposes synthetic Administrative Service duality Index(ASQI) using fuzzy set theory and analytic hierarchy process to evaluate the service qualify in subjective environment. In ASQI model, Fuzzy set theory helps to measure the ambiguity of concepts that are relative to human being's subjective judgement. Also, this study utilizes AHP method to evaluate the preference weights of service quality dimensions (tangibility, reliability, responsiveness, assurance, empathy) for customers.

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.79-86
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• 2021

Alzheimer's is a chronic progressive disease which exhibits varied symptoms and behavioural traits from person to person. The deterioration in cognitive abilities is more noticeable through their Activities and Instrumental Activities of Daily Living rather than biological markers. This information discussed in social media communities was collected and features were extracted by using the proposed fuzzy logic based algorithm to address the uncertainties and imprecision in the data reported. The data thus obtained is used to train machine learning models in order to predict the longevity of the patients. Models built on features extracted using the proposed algorithm performs better than models trained on full set of features. Important findings are discussed and Support Vector Regressor with RBF kernel is identified as the best performing model in predicting the longevity of Alzheimer's patients. The results would prove to be of high value for healthcare practitioners and palliative care providers to design interventions that can alleviate the trauma faced by patients and caregivers due to chronic diseases.

• Journal of Digital Contents Society
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• v.19 no.7
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• pp.1365-1372
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• 2018

The purpose of this study is to analyze the importance of the determinants of housing sales agency's role in the sale of apartment housing. For this purpose, a hierarchical decision model was constructed to understand the role and importance of the sales agency. The analytical variable items structured by the research model were set up through literature review, precedent research, and expert brainstorming. The questionnaire consisted of two comparisons for AHP analysis and the importance of absolute importance for fuzzy analysis. Afterwards, the work of correcting the importance was carried out. As a result of the analysis, it was found that the contractor prioritized the sale conditions and the sales agency had priority over the planning for the sale. As a result of analysis, planning of customer pre-sale counseling data, planning of client subscription and contract maximization plan, planning method of advertisement public media method were found to be the most important factors. The results of measurement of absolute importance(fuzzy) & relative importance(,AHP) showed similar tendency. Therefore, it can be seen that the timing of the model house operation is an important period in which the subscription rate depends on the role of the sales agency and the marketing strategy.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.438-442
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• 2003

For an efficient sliding mode control system stability and chattering avoidance should be guaranteed. A continuation method using boundary layer is well known as one solution for this. However since not only model uncertainties and disturbances but also control task itself is variable. it is practically impossible to set controller parameters - control discontinuity, control bandwidth, boundary layer thickness - in advance. In this paper first an adaptation law of control discontinuity is introduced to assure system stability and then fuzzy logic based tuning algorithm of design parameters is applied based on monitored performance indices of tracking error, control chattering, and model precision. In the end maximum control bandwidth not exciting unmodeled dynamics and minimum control discontinuity, boundary layer thickness making system stable and free of chattering are found respectively. This eliminates control chattering and enhances control accuracy as much as possible under given control situation. In order to demonstrate the validity of the proposed algorithm safe headway maintenance control for autonomous transportation system is simulated. The control results show that the proposed algorithm guarantees system stability all the time and tunes control parameters consistently and in consequence implements an efficient control in terms of both accuracy and actuator chattering.