• International Journal of Fuzzy Logic and Intelligent Systems
• /
• 제6권2호
• /
• pp.167-172
• /
• 2006

As ubiquitous devices are fast spreading, the communication problem between humans and these devices is on the rise. The use of context is important in interactive application such as handhold and ubiquitous computing. Context is not crisp data, so it is necessary to introduce the fuzzy concept. The proxity relation is represented by the degree of closeness or similarity between data objects of a scalar domain. A context manager of context-awareness system evaluates imprecise queries with the proximity relations. in this paper, a systematic proximity elicitation method are proposed. The proposed generation method is simple and systematic. It is based on the well-known fuzzy set theory and applicable to the real world applications because it has tuning parameter and weighting factor. The proposed representations of proximity relation is more efficient than the ordinary matrix representation since it reflects some properties of a proximity relation to save space. We show an experiments of quantitative calculate for the proximity relation. And we analyze the time complexity and the space occupancy of the proposed representation method.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제17권10호
• /
• pp.2701-2717
• /
• 2023

In this paper, a hybrid fuzzy-based method is suggested for determining India's best system for power generation. This suggested approach was created using a fuzzy-based combination of the Giza Pyramids Construction (GPC) and Recalling-Enhanced Recurrent Neural Network (RERNN). GPC is a meta-heuristic algorithm that deals with solutions for many groups of problems, whereas RERNN has selective memory properties. The evaluation of the current load requirements and production profile information system is the main objective of the suggested method. The Central Electricity Authority database, the Indian National Load Dispatch Centre, regional load dispatching centers, and annual reports of India were some of the sources used to compile the data regarding profiles of electricity loads, capacity factors, power plant generation, and transmission limits. The RERNN approach makes advantage of the ability to analyze the ideal power generation from energy data, however the optimization of RERNN factor necessitates the employment of a GPC technique. The proposed method was tested using MATLAB, and the findings indicate that it is effective in terms of accuracy, feasibility, and computing efficiency. The suggested hybrid system outperformed conventional models, achieving the top result of 93% accuracy with a shorter computation time of 6814 seconds.

• 한국지능시스템학회논문지
• /
• 제17권2호
• /
• pp.185-189
• /
• 2007

본 연구에서는 T-S 퍼지시스템으로 모델된 불확실한 시변 파라메터를 갖는 비선형 시스템의 고장검출 시스템 설계법을 제안한다. 이를 위하여 퍼지시스템에 대한 소인수 분해를 정의하고 좌 소인수를 이용하여 오차발생기를 설계한다. 오차발생기의 출력으로부터 고장검출을 판정하는 검출기준을 제시한다. 제시된 방법의 효용성을 입증하기 위하여 역도립 진자시스템에 적용하여 컴퓨터 모의실험을 수행한다.

• 제어로봇시스템학회논문지
• /
• 제9권5호
• /
• pp.384-389
• /
• 2003

We propose a hierarchically structured navigation algorithm for multiple mobile robots under unknown dynamic environment based on fussy-neural algorithm. The proposed algorithm consists of two basic layers. The lower layer consists of two parts such as fuzzy algorithm for goal approach and fuzzy-neural algorithm for obstacle avoidance. The upper layer which is basically fuzzy algorithm adjusts the magnitude of the weighting factor depending on the environmental situation. In addition, The proposed algorithm provides an efficient method to escape local mimimum points as shown in the simulation result. The efficacy of the proposed method is demonstrated via some simulations.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2000년도 하계학술대회 논문집 D
• /
• pp.3004-3006
• /
• 2000

In this paper, we propose an optimal design method of Fuzzy-Neural Networks model with parallel structure for complex and nonlinear systems. The proposed model is consists of a multiple number of FNN connected in parallel. The proposed FNNs with parallel structure is based on Yamakawa's FNN and it uses simplified inference as fuzzy inference method and Error Back Propagation Algorithm as learning rules. We use a HCM clustering and GAs to identify the structure and the parameters of the proposed model. Also, a performance index with a weighting factor is presented to achieve a sound balance between approximation and generalization abilities of the model. To evaluate the performance of the proposed model. we use the time series data for gas furnace and the numerical data of nonlinear function.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1998년도 제13차 학술회의논문집
• /
• pp.215-220
• /
• 1998

In order to optimize fuzzy model, we use the optimal algorithm with a hybrid type in the identification of premise parameters and standard least square method in the identification of consequence parameters of a fuzzy model. The hybrid optimal identification algorithm is carried out using a genetic algorithm and improved complex method. Also, the performance index with weighting factor is proposed to achieve a balance between the insults of performance for the training and testing data. Several numerical examples are used to evaluate the performance of the proposed model.

• 한국지능시스템학회:학술대회논문집
• /
• 한국퍼지및지능시스템학회 2006년도 추계학술대회 학술발표 논문집 제16권 제2호
• /
• pp.356-361
• /
• 2006

본 연구에서는 T-S 퍼지시스템으로 모델된 불확실한 시변 파라메터를 갖는 비선형 시스템의 고장검출 시스템 설계법을 제안한다. 이를 위하여 퍼지시스템에 대한 소인수 분해를 정의하고 좌 소인수를 이용하여 오차발생기를 설계한다. 오차 발생기의 출력으로부터 고장검출을 판정하는 검출기준을 제시한다. 제시된 방법의 효용성을 입증하기 위하여 역도립 진자시스템에 적용하여 컴퓨터 모의실험을 수행한다.

• 대한전기학회논문지:시스템및제어부문D
• /
• 제49권11호
• /
• pp.599-609
• /
• 2000

The new design methodology of a hybrid fuzzy controller by means of the genetic algorithms is presented. First, a hybrid fuzzy controller(HFC) related to the optimal estimation of control parameters is proposed. The control input for the system in the HFC combined PID controller with fuzzy controller is a convex combination of the FLC's output and PID's output by a fuzzy variable, namely, membership function of weighting coefficient. Second, an auto-tuning algorithms utilizing the simplified reasoning method and genetic algorithms is presented to automatically improve the performance of hybrid fuzzy controller. Especially, in order to auto-tune scaling factors and PID parameters of HFC using GA, three kinds of estimation modes such as basic, contraction, and expansion mode are effectively utilized. The proposed HFC is evaluated and discussed to show applicability and superiority with the and of three representative processes.

• 한국지능시스템학회:학술대회논문집
• /
• 한국퍼지및지능시스템학회 2006년도 춘계학술대회 학술발표 논문집 제16권 제1호
• /
• pp.85-89
• /
• 2006

구간값 퍼지집합은 일반적인 퍼지집합보다 언어적인 의사결정 절차에서 매핑의 정확성과 계산의 효율성이 뛰어나고, 규칙의 가중치는 패턴 분류문제에서 분류 경계를 효율적으로 조정할 수 있다는 장점을 가지고 있다. 따라서 본 논문에서는 퍼지규칙 기반 분류방법을 구간값 퍼지규칙 기반 분류방법으로 확장하고 규칙의 가중치를 고려한 분류방법을 제안한다. 모의실험에서는 일반 퍼지집합에서 규칙 가중치를 고려한 분류방법과 구간값 퍼지집합에서 규칙 가중치를 고려한 분류방법을 비교하였다.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2005년도 제36회 하계학술대회 논문집 A
• /
• pp.196-198
• /
• 2005

In this paper, we design the Thyristor Controlled Series Capacitor(TCSC) supplementary controller for oscillation damping of power system. Here the supplementary controller is designed as a fuzzy logic-based precompensation approach for TCSC. This scheme is easily implemented simply by adding a fuzzy precompensator to an existing TCSC. And we optimize the fuzzy precompensator with a genetic algorithm for complements the demerit such as the difficulty of the component selection of fuzzy controller, namely, scaling factor, membership function and control rules. Simulation results show that the proposed control technique is superior to a conventional method in dynamic responses over the wide range of operating conditions and is convinced robustness and reliableness in view of structure.