• Journal of the Korean Institute of Intelligent Systems
• /
• v.19 no.5
• /
• pp.595-602
• /
• 2009

Fuzzy rules, which represent the behavior of their system, are sensitive to fuzzy clustering techniques. If the classification abilities of such clustering techniques are improved, their systems can work for the purpose more accurately because the capabilities of the fuzzy rules and parameters are enhanced by the clustering techniques. Thus, this paper proposes a new hierarchically structured clustering algorithm that can enhance the classification abilities. The proposed clustering technique consists of two clusters based on correlationship and statistical characteristics between data, which can perform classification more accurately. In addition, this paper uses difference data sets to reflect the patterns and regularities of the original data clearly, and constructs multiple fuzzy systems to consider various characteristics of the differences suitably. To verify effectiveness of the proposed techniques, this paper applies the constructed fuzzy systems to the field of time series prediction, and performs prediction for nonlinear time series examples.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.17 no.1
• /
• pp.7-12
• /
• 2007

In this paper, we introduce an approach to design multi-fuzzy controllers for the superheat and the low pressure that have an influence on energy efficiency and stabilization of aft conditioning system. Air conditioning system is composed of compressor, condenser several evaporators and several expansion valves. It is quite difficult to control the air conditioning system because the change of the refrigerant condition give an impact on the overall air conditioning system. In order to solve the drawback, we design multi-fuzzy controllers which control simultaneously both three expansion valve and one compressor for the superheat and the low pressure of air conditioning system. The proposed multi fuzzy controllers are given as two kinds of controller types such as a continuous simplified fuzzy inference type and a discrete fuzzy lookup_table type. Here the scaling factors of each fuzzy controller ate efficiently adjusted by veal coding type Genetic Algorithms. The values of performance index of the conventional type are compared with the simulation results of discrete lookup_table type and continuous simplified inference type.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2002.05a
• /
• pp.245-251
• /
• 2002

본 논문에서는 상대적으로 큰 퍼지 엔트로피를 갖는 입력-출력 데이터 집단에 다중 회귀 분석을 적용하여 다차원 평면 클러스터를 생성하고, 이 클러스터를 새로운 퍼지 모델의 규칙으로 추가한 후 퍼지 모델 파라미터의 개략 동조와 정밀 동조를 수행하는 자기구성 퍼지 모델링을 제안한다. Weighted recursive least squared 알고리즘과 fuzzy C-regression model 클러스터링에 의해 퍼지 모델의 파라미터를 개략적으로 동조한 후 gradient descent 알고리즘에 의해 파라미터를 정밀 동조하면서 감수분열 유전 알고리즘을 이용하여 최적의 학습률을 탐색한다. 그리고 자기 구성 퍼지 모델링 기법을 이용하여 Box-Jenkins의 가스로 데이터, 다변수비선형 정적 함수의 데이터와 하수 처리 활성오니 공정의 모델링을 수행하고, 기존의 방법에 의한 모델링 결과와 비교하여 그 성능을 입증한다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2006.05a
• /
• pp.148-151
• /
• 2006

본 논문에서 얼굴과 홍채 데이터를 사용하여 다중생체시스템에 기반한 스테가노그라피 구현을 제안한다. 이를 위해, 얼굴과 홍채 인식 기반의 다중생체인식을 구성하였다. 여기서, 홍채의 특징벡터는 디지털 워터마킹 기법을 이용하여 얼굴 이미지 안에 숨기게 된다. 얼굴과 홍채의 인식시스템은 퍼지집합 이론과 LDA 기법이 결합하여 확장한 Fuzzy-LDA(Fuzzy-Based Linear Discriminant Analysis)기법을 제안한다. 최종적으로 디지털 워터마킹 기법을 적용하여 얼굴이미지 안에 홍채 정보를 삽입하고 얼굴 데이터와 홍채 데이터를 통한 다중생체인식을 구성하였으며, 최종적으로 생체데이터 인식율의 ROC 곡선을 통해 제안된 워터마킹 기법의 좋은 성능을 확인하였고, 얼굴 인식율을 통해 워터마킹된 얼굴 영상과 원본 얼굴 영상을 비교하였다. 다양한 실험을 통해 제안된 기법이 다중생체시스템을 보호하고 효과적으로 사용 될 수 있음을 확인 할 수 있다.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.12 no.6
• /
• pp.549-553
• /
• 2002

This paper develops knowledge-based multiple fuzzy rules for researcher-selection by automatic ranking process. Inference rules for researcher-selection are created, then the multiple fuzzy rule system with max-min inference is applied. The way to handle for selection standards according to a certain criteria in dynamic manner, is also suggested in a simulation model. The model offers automatic, fair, and trust decision for researcher-selection processing.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.13 no.8
• /
• pp.1483-1490
• /
• 2009

This parer is presented multiple path-planning of unmanned autonomous forklift using modified genetic algorithm and fuzzy inference system. There are a task-level feedback method and a method that path is dynamically replaned in realtime while the autonomous vehicles are moving by means of an optimal algorithm for existing multiple path-planning. However, such methods cause malfunctions and inefficiency in the sense of time and energy, and path-planning should be dynamically replanned in realtime. To solve these problems, we propose multiple path-planning using modified genetic algorithm and fuzzy inference system and show the performance with autonomous vehicles. For experiment, we designed and built two autonomous mobile vehicles that equipped with the same driving control part used in actual autonomous forklift, and test the proposed multiple path-planning algorithm. Experimental result that actual autonomous mobile vehicle, we verified that fast optimized path-planning and efficient collision avoidance are possible.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.19 no.3
• /
• pp.337-342
• /
• 2009

This paper concerns delay-range-dependent robust stability and stabilization for time-delay nonliner system via T-S fuzzy model approach. The time delay is assumed to be a time-varying continuous function belonging to a given range. On the basis of a novel Lyapunov-Krasovskii functional, which includes the information of the range, delay-range-dependent stability criteria are established in terms of linear matrix inequality. It is shown that the new criteria can provide less conservative results than some existing ones. Moreover, the stability criteria are also used to design the stabilizing state-feedback controllers. Numerical examples are given to demonstrate the applicability of the proposed approach.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.10 no.5
• /
• pp.409-416
• /
• 2000

In the shared-memory mutiprocessor systems, shared processing techniques such as time-sharing, space¬sharing, and gang-scheduling are used to improve the overall system utilization for the parallel operations. Recently, LLPC(Loop-Level Process Control) allocation technique was proposed. It dynamically adjusts the needed number of processors for the execution of the parallel code portions based on the current system load in the given job. This method allocates as many available processors as possible, and does not save any processors for the parallel sections of other later-arriving applications. To solve this problem, in this paper, we propose a new processor allocation technique called FPA(Fuzzy Processor Allocation) that dynamically adjusts the number of processors by fuzzifYing the amounts ofueeded number of processors, loads, and estimated execution times of job. The proposed method provides the maximum possibility of the parallism of each job without system overload. We compare the performances of our approaches with the conventional results. The experiments show that the proposed method provides a better performance.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.12 no.6
• /
• pp.497-502
• /
• 2002

The problem of maneuvering target tracking has been studied in the field of the state estimation over decades. The Kalman filter has been widely used to estimate the state of the target, but in the presence of a maneuver, its performance may be seriously degraded. In this paper, to solve this problem and track a maneuvering target effectively, a DNA coding-based interacting multiple model (DNA coding-based W) method is proposed. The proposed method can overcome the mathematical limits of conventional methods by using the fuzzy logic based on DNA coding method. The tracking performance of the proposed method is compared with those of the adaptive IMM algorithm and the GA-based IMM method in computer simulations.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2010.07a
• /
• pp.51-54
• /
• 2010

본 논문에서는 포텐셜 필드 방법과 퍼지로직 시스템을 이용하여 멀티 모바일 로봇의 충돌회피를 위한 경로계획을 연구한다. 잘 알려진 포텐셜 필드 방법은 멀티 모바일 로봇 시스템에 있어서 각각의 로봇에 대한 전역경로를 계획하기 위해 사용되었으며, 퍼지로직 시스템은 각 로봇에 근접하는 혹은 진행하는 로봇의 경로를 가로막는 장애물과의 충돌을 피하고 안전하게 목적지에 도달하기 위한 지역경로를 계획하기 위해 이용되었다.