• Korean Journal of Food Science and Technology
• /
• v.26 no.6
• /
• pp.776-780
• /
• 1994

Fuzzy reasoning was applied to sensory evaluation of cooked rice. A sensory attribute diagnostics was done in terms of tour kinds of attributes-texture, taste, odor and appearance which determine overall palatability. First, rating for the contribution level of each attribute to the overall palatability was asked as one of five scales-very important, important, moderate, slight and very slight. Secondly, the preference level of each attribute for a cooked rice sample was asked as one of five hedonic scales-excellent, good, fair, poor and very poor. Thirdly, the results of the scales were converted into fuzzy values and operated by fuzzy reasoning. Finally, the contribution and preference levels of the attributes were composed to infer the overall palatability of cooked rice sample.

• The KIPS Transactions:PartB
• /
• v.17B no.2
• /
• pp.163-168
• /
• 2010

A linguistic case-based fuzzy reasoning (LCBFR) based on standardized parametric membership functions (SPMF) is proposed. It provides an efficient mechanism for a fuzzy reasoning within linear time complexity. Thus, it can be used to improve the speed of fuzzy reasoning. In the process of LCBFR, linguistic case indexing and retrieval based on SPMF is suggested. It can be processed relatively fast compared to the previous linguistic approximation methods. From the engineering viewpoint, it may be a valuable advantage.

• Journal of KIISE:Databases
• /
• v.27 no.2
• /
• pp.141-150
• /
• 2000

There are three significant drawbacks in extant fuzzy rule-based expert system languages. First, they lack the functionality of composite object inference. Second, they do not support fuzzy reasoning semantically easy to understand and conceptually simple to use. Third, knowledge representation and reasoning style of their model have a great semantic gap with those of current database models. Therefore, it is very difficult for the two models to be seamlessly integrated with each other. This paper provides the formal specification of a fuzzy object inference model to solve the three drawbacks. GIS(Geographic Information System) application domain is used to demonstrate that our model naturally models complex GIS information in terms of composite objects and successfully performs fuzzy inference between them.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.8 no.3
• /
• pp.41-49
• /
• 1998

Agent, as a independent module, exchanges knowledge & information which are classified to their characteristics according to shared protocol. i.e. Agent Communication Language(AC1,). Fuzzy inference system represents the experiential knowledge as li~~guisticco ntrol rule and enables us to execute the knowledge using fuzzy inference. This study tries connecting fuzzy inference system with agent-based system and inspects applicability to hull form design through inferring principle dimension and hull form coefficients.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.33B no.12
• /
• pp.84-94
• /
• 1996

In this work, a fuzzy petri net model for modeling a general form of fuzzy production system which consists of chaining fuzzy production rules and so requires multistage reasoning process is presented. For the obtained fuzzy petri net model, the net will be transformed into some matrices, and also be systematically led to an algebraic form of a state equation. Since it is fond that the approximate reasoning process in fuzzy systems corresponds to the dynamic behavior of the fuzzy petri net, it is further shown that the multistage reasoning process can be carried out by executing the state equation.

• Journal of the Korean Institute of Telematics and Electronics C
• /
• v.36C no.12
• /
• pp.69-77
• /
• 1999

This paper describes the design of fuzzy digital PID controller using simplified indirect inference method. First, the fuzzy digital PID controller is derived from the conventional continuous time linear digital PID controller. Then the fuzzification, control-rule base, and defuzzification using SIM in the design of the fuzzy digital controller are discussed in detail. The resulting controller is a discrete time fuzzy version of the conventional digital PID controller, which has the same linear structure, but are nonlinear functions of the input signals. The proposed controller enhances the self-tuning control capability, particularly when the process to be controlled is nonlinear. When the SIM is applied, the fuzzy inference results can be calculated with splitting fuzzy variables into each action component and are determined as the functional form of corresponding variables. So the proposed method has the capability of the high speed inference and adapting with increasing the number of the fuzzy input variables easily. Computer simulation results have demonstrated the superior to the control performance of the one proposed by D. Misir et al.

• Journal of the Korea Society of Computer and Information
• /
• v.16 no.10
• /
• pp.63-71
• /
• 2011

We present a method to modify the recognition of neural networks by the fuzzy inference in a handwritten digit recognition with large deformations, and we verified the method by the experiment. The neural networks take long time in learning and recognize 100% on the learning pattern. But the neural networks don't show a good recognition on the testing pattern. So, we apply the modified method as the fuzzy inference. As a result, the recognition and false recognition of neural networks was improved 90.2% and 9.8% respectively at 89.6% and 10.4% initially. This approach decreased especially the false recognition on digit 3, 5. We used the density of digit to extract the fuzzy membership function in this experiment. But, because the handwritten digit have varified input patterns, we will get a better recognition by extracting varifed characteristics and applying the composite fuzzy inference. We also propose the application of fuzzy inference on matching the input pattern, than applying strictly the fuzzy inference.

• The Journal of the Korea Contents Association
• /
• v.11 no.4
• /
• pp.74-82
• /
• 2011

To do fuzzy modelling of a nonlinear process needs to analyze the characteristics of input-output of fuzzy inference systems according to the division of entire input spaces and the fuzzy reasoning methods. For this, fuzzy model is expressed by identifying the structure and parameters of the system by means of input variables, fuzzy partition of input spaces, and consequence polynomial functions. In the premise part of the fuzzy rules Min-Max method using the minimum and maximum values of input data set and C-Means clustering algorithm forming input data into the clusters are used for identification of fuzzy model and membership functions are used as a series of triangular, gaussian-like, trapezoid-type membership functions. In the consequence part of the fuzzy rules fuzzy reasoning is conducted by two types of inferences such as simplified and linear inference. The identification of the consequence parameters, namely polynomial coefficients, of each rule are carried out by the standard least square method. And lastly, using gas furnace process which is widely used in nonlinear process we evaluate the performance and the system characteristics.

• Journal of the Earthquake Engineering Society of Korea
• /
• v.5 no.2
• /
• pp.1-11
• /
• 2001

내진성능평가 시스템은 구조시스템의 합리적인 분류, 적절한 평가 기준, 그리고 종합적인 평가방법을 포함하여야한다. 외국의 현행 내진성능 평가방법은 데이터의 수집과 주요 평가 항목을 위한 약산식 그리고 평가 점수를 이용하여 전문가의 판단에 근거한 평가 방법을 제시하고 있다. 본 연구는 국내 건축구조물에 예비 내진평가 방법에 중점을 두고 퍼지추론 시스템에 근거한 내진평가방법의 전형을 개발한다. 평가항목의 위계는 건무의 수직, 수평방향을 불규칙성, 비대칭성, 여용성, 그리고 건물 연한을 포함한 전체적인 특성과 부재 단계에서의 상세한 평가 항목으로 구성한다. 퍼지추론방법에 대한 기존의 연구결과를 근허가혀 이용한 내진성능 평가방법에 적절히 적용하기 위하여 4가지 주요 모듈을 설정한다. (1) 퍼지 입력 (2) 퍼지에 근거한 규칙기반 (3) 퍼지추론, 그리고 (4) 퍼지출력으로 구성된다. 더욱이 개별적인 성능 수준에 종합적인 평가지수를 끌어내기 위하여 퍼지추론방법을 적용하였다.

• The KIPS Transactions:PartB
• /
• v.14B no.4
• /
• pp.281-286
• /
• 2007

This paper proposes an intelligent context awareness middleware(ICAM) for Ubiquitous Computing Environment. In this paper we have researched about the context awareness middleware. The ICAM model is based on ontology that efficiently manages analyses and learns about various context information and can provide intelligent services that satisfy the human requirements. Therefore, various intelligent services will improve user's life environment. We also describe the current implementation of the ICAM for service adaptation based on fuzzy inference that help applications to adapt their ubiquitous computing environments according to rapidly changing. For this, after defining the requirements specifications of ICAM, we have researched the inferred processes for the higher level of context awareness. The Fuzzy Theory has been used in process of inferences, and showed constructing the model through the service process. Also, the proposed fuzzy inferences has been applied to smart Jacky, and after inferring the fuzzy values according to the change of temperature, showed the adaptability of Smart Jacky according to the change of surroundings like temperature as showing the optimal value of status.