• Journal of the Korean Institute of Intelligent Systems
• /
• v.11 no.2
• /
• pp.101-108
• /
• 2001

본 논문에서는 배전선로에서 발생하는 여러 고장유형을 판별하기 위해서 적응형 퍼지추론 시스템을 적용하는 새로운 기법을 제시하였다. 배전선로의 고장과 고장유사현상 데이터를 추출하기 위해서 EMTP를 이용하여 RL부하, 아크로부하, 컨버터부하가 있는 배전계통을 구성하고 여러 형태의 고장과 고장유사현상에 대해 시뮬레이션을 하였다. 이를 통해 얻은 전류 파형으로부터 기본파성분, 영상분전류, 짝수 고조파성분의 합, 홍수 고조파성분의 합, 그리고 비정규 고조파성분의 합의 5개의 입력변수를 추출하고 학습을 통해서 각 입력변수의 소속함수의 소속도를 자동으로 결정하였다. 이 적응형 퍼지추론 시스템을 이용한 기법을 평가하기 위해서 학습시와 다른 고장상황을 모의하여 얻은 데이터와 실증시험 데이터를 이용하였다. 결과적으로 제안한 기법은 배전선로에서 발생하는 고장유형을 빠르고 정확하게 판별할 수 있었다.

• 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.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2005.11a
• /
• pp.1203-1206
• /
• 2005

현재 무선 센서 네트워크에서 에너지 효율성을 고려한 많은 라우팅 프로토콜이 연구되고 있다. 하지만 기존에 제안된 무선 센서 네트워크 라우팅 프로토콜은 특정 상황 및 응용에 특화되어 있기 때문에, 동적으로 변화하는 네트워크 상에서는 데이터 전달의 정확성 및 에너지 효율성이 떨어지는 문제점이 있다. 본 연구에서는 이러한 문제점을 개선하기 위하여 퍼지 추론 시스템을 이용한 라우팅 프로토콜 선택 기법과 라우팅 프로토콜의 동적 배치 기법을 기반으로 한 퍼지 적응형 라우팅(FAR) 알고리즘을 제안한다.

• Journal of Bio-Environment Control
• /
• v.20 no.3
• /
• pp.169-175
• /
• 2011

The adaptive neuro-fuzzy inference system (ANFIS) based automatic control system framework was proposed for integrated environment management of ubiquitous plant factory which can collect information of crop cultivation environment and monitor it in real-time by using various environment sensors. Installed wireless sensor nodes, based on the sensor network, collect the growing condition's information such as temperature, humidity, $CO_2$, and the control system is to monitor the control devices by using ANFIS. The proposed automatic control system provides that users can control all equipments installed on the plant factory directly or remotely and the equipments can be controlled automatically when the measured values such as temperature, humidity, $CO_2$, and illuminance deviated from the decent criteria. In addition, the better quality of the agricultural products can be gained through the proposed automatic control system for plant factory.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.14 no.1
• /
• pp.30-37
• /
• 2000

We studied on acquiring of transfer function and tuning of 2-DOF PID controller using ANFIS for the optimum control to turbine's variables variety. Since the shape of a membership function in the ANFIS based on the characteristics of plant. ANFIS based control method is effective for plant that its variable vary. On the other hand, a start-up time is very short and its variable's value for optimal start-up in gas turbine should be varied, but it is very difficult for such a controller to design. In this paper, we tune 2-DOF PID controller after apply a ANFIS to the operating data of Gun-san gas turbine and verify the characteristics. Its results is compared to the conventional PID controller and discuss. We expect this method will be used for another process because it is studied on the real operating data.

• The Journal of Korean Association of Computer Education
• /
• v.6 no.4
• /
• pp.95-113
• /
• 2003

We introduce an AFES(Adaptive Fuzzy Evaluation System) that applies an evaluation system used to existing LCMS(Learning Contents Management System) to a fuzzy reasoning rule. The AFES confers a course level on the learner through a fuzzy diagnostic evaluation before the learner enters a learning course. After the learner completes a learning course through the tailored learning path that is suitable for the learner's level, the AFES confers a final grade on the learner by means of fuzzy final evaluation. The biggest characteristic of the AFES is a grade rule of the final grade. Although different learners get the same number of correct answers to the same number of Questions, AFES flexibly confers the different final grade on the learner by means of the number of 125's fuzzy reasoning rules.

• Journal of Biomedical Engineering Research
• /
• v.24 no.5
• /
• pp.465-471
• /
• 2003

The purpose of this research was to evaluate chronic stress using physiological parameters. Wistar rats were exposed to the sound stress for 14 days. Biosignals were acquired hourly. To develop a fuzzy inference system which can integrate physiological parameters. the parameters of the system were adjusted by the adaptive neuro-fuzzy inference system. Of the training dataset, input dataset was the physiological parameters from the biosignals and output dataset was the target values from the cortisol production. Physiological parameters were integrated using the fuzzy inference system. then 24-hour results were analyzed by the Cosinor method. Chronic stress was evaluated from the degree of circadian rhythm disturbance. Suppose that the degree of stress for initial rest period is 1. Then. the degree of stress after 14-day sound stress increased to 1.37, and increased to 1.47 after the 7-day recovery period. That is, the rat was exposed to 37%-increased amount of stress by the 14-day sound and did not recover after the 7-day recovery period.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.31 no.5B
• /
• pp.405-414
• /
• 2011

The adaptive network-based fuzzy inference system (ANFIS) which had a success for time series prediction and system control was applied for modeling the hourly runoff in the Gapcheon watershed. The ANFIS used the antecedent rainfall and runoff as the input. The ANFIS was trained by varying the various simulation factors such as mean areal rainfall estimation, the number of input variables, the type of membership function and the number of membership function. The root mean square error (RMSE), mean peak runoff error (PE), and mean peak time error (TE) were used for validating the ANFIS simulation. The ANFIS predicted runoff was in good agreement with the measured runoff and the applicability of ANFIS for modelling the hourly runoff appeared to be good. The forecasting ability of ANFIS up to the maximum 8 lead hour was investigated by applying the different input structure to ANFIS model. The accuracy of ANFIS for predicting the hourly runoff was reduced as the forecasting lead hours increased. The long-term predictability of ANFIS for forecasting the hourly runoff at longer lead hours appeared to be limited. The ANFIS might be useful for modeling the hourly runoff and has an advantage over the physically based models because the model construction of ANFIS based on only input and output data is relatively simple.

• Proceedings of the Korea Society for Simulation Conference
• /
• 2005.11a
• /
• pp.25-29
• /
• 2005

무선 센서 네트워크에서 센서 노드는 배터리와 같은 제한적인 전원을 가지고 있기 때문에, 센서 노드의 수명을 연장하기 위하여 에너지 효율성을 고려한 다양한 라우팅 프로토콜이 연구되고 있다. 하지만 기존에 제안된 라우팅 프로토콜들은 특정 상황 및 응용에 특화되어 있기 때문에, 하드웨어에 내장시킨 단일 라우팅 프로토콜만으로는 동적으로 변화하는 네트워크 상에서 에너지 효율성을 보장할 수 없다는 문제점이 있다. 본 연구에서는 이러한 문제점을 개선하기 위하여 퍼지 추론 시스템을 기반으로, 다양한 후보 라우팅 프로토콜 중 현재 네트워크 상황에 적합한 라우팅 프로토콜을 선택하여, 이를 동적으로 센서 노드에 적재 혹은 교체하도록 하는 퍼지 기반의 적응형 라우팅 알고리즘을 제안한다. 또한 시뮬레이션을 수행하여 동적인 네트워크 상황 하에서 제안된 라우팅 알고리즘을 사용한 경우가 기존의 단일 라우팅 프로토콜만을 사용한 경우보다 에너지 효율적임을 검증한다.

• Journal of Ocean Engineering and Technology
• /
• v.12 no.3 s.29
• /
• pp.96-102
• /
• 1998

This paper presents to create a SAC(Sectional Area Curve) using an ANFIS(Adaptive-Network-based Fuzzy Inference System). First, it defines SACs of parent ships by using a B-spline approximation and a genetic algorithm and accumulates a database about SAC's control points. Second, it learns an ANFIS from parent ship data, which are related with principal dimensions and SAC's control points. This process is to model an ANFIS for SAC inferreice. When an ANFIS modeling is completed, we can determine a SAC through an ANFIS inferring.