• 동력기계공학회지
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• 제22권1호
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• pp.18-24
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• 2018

This paper focuses on systematic design about the membership ranges of the main design factors such as control error, control error rate, and sampling time for the fuzzy logic control of the variable speed drive refrigeration cycle. The upper and the lowest limit of the membership ranges are set up from the data of static characteristics obtained by experiments. Three kinds of membership ranges on the control error and the control error rate are tested by experiments. Especially, an effect of sampling time on control performance is also investigated in the same way. Experimental data showed the control error rate and the sampling time strongly effected on the control performance of the refrigeration cycle with a variable speed drive.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1995년도 하계학술대회 논문집 B
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• pp.813-816
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• 1995

The shape and width of fuzzy membership function has an effect on performance of fuzzy controller. In this paper, neuro-fuzzy controller is proposed to improve the control performance of fuzzy controller. It has membership function, that is adapt to plant constant by using trained neural network. This neural network has been trained with back propagation algorithm. To show the effectiveness of proposed neuro-fuzzy controller with adaptive membership function, it is applied to plant (dead time + 1st order) with various plant constant.

• 대한인간공학회지
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• 제20권2호
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• pp.29-46
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• 2001

This study is about the modeling of comfort feeling structure in indoor environments. To represent the degree of practical comfort feeling level in an environment, we measured elements of human sense and resultant elements of comfort feeling such as coziness, refreshment, and freshness with physical values(temperature, illumination, noise. etc.). The relationships of elements of human sense and elements of comfort feeling were formulated as a fuzzy model. And a hybrid-neural network with three layers were designed where obtained from fuzzy membership function values of the elements of human sense were used as inputs, and given as fuzzy membership function values of resultant elements of comfort feeling were used as outputs. Both kinds of fuzzy membership function values were obtained from physical values. The network was trained by measured data set. The proposed hybrid-neural network were tested and proposed a more realistic model of comfort feeling structure in indoor environments.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 하계학술대회 논문집 B
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• pp.1021-1023
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• 1996

This paper proposes a design of self-tuning fuzzy rules and membership functions based on genetic algorithms. Sub-optimal fuzzy rules and membership functions are found by using genetic algorithms. Genetic algorithms are used for tuning fuzzy rules and membership functions. A arbitrary speed trajectories are selected for the reference input of the proposed methods. Experimental results show the good performance in the DC motor control system with the self-tuning fuzzy controller based on genetic algorithms.

• 한국지능시스템학회논문지
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• 제12권3호
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• pp.261-268
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• 2002

This paper represents that auto tunings of membership functions and weights in the fuzzy neural networks are effectively performed by immune algorithm. A number of hybrid methods in fuzzy-neural networks are considered in the context of tuning of learning method, a general view is provided that they are the special cases of either the membership functions or the gain modification in the neural networks by genetic algorithms. On the other hand, since the immune network system possesses a self organizing and distributed memory, it is thus adaptive to its external environment and allows a PDP (parallel distributed processing) network to complete patterns against the environmental situation. Also, it can provide optimal solution. Simulation results reveal that immune algorithms are effective approaches to search for optimal or near optimal fuzzy rules and weights.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제5권9호
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• pp.1668-1683
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• 2011

The importance of secure communication between only legitimate group members in ad hoc networks has been growing in recent years. Due to the ad hoc nature the scalability on dynamic membership change is a major concern. However, the previous models require at least O(log n) communication cost for key update per each membership change, which imposes a heavy burden on the devices. In this paper we present a scalable model that supports communication-efficient membership change in ad hoc networks by exclusionary keys and RSA functions. The multicast cost for key update is extremely low, that is O(1) , and one-to-one communications occur mostly in neighboring devices.

• Journal of Information Processing Systems
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• 제15권3호
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• pp.550-569
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• 2019

We propose approaches for improving Bloom filter in terms of false positive probability and membership query speed. To reduce the false positive probability, we propose special type of additional Bloom filters that are used to handle false positives caused by the original Bloom filter. Implementing the proposed approach for a routing table lookup, we show that our approach reduces the routing table lookup time by up to 28% compared to the original Bloom filter by handling most false positives within the fast memory. We also introduce an approach for improving the membership query speed. Taking the hash table-like approach while storing only values, the proposed approach shows much faster membership query speed than the original Bloom filter (e.g., 34 times faster with 10 subsets). Even compared to a hash table, our approach reduces the routing table lookup time by up to 58%.

• Journal of information and communication convergence engineering
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• 제19권1호
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• pp.54-60
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• 2021

Various digital devices were supplied throughout the Fourth Industrial Revolution. Accordingly, the importance of data processing has increased. Data processing significantly affects equipment reliability. Thus, the importance of data processing has increased, and various studies have been conducted on this topic. This study proposes a modified Gaussian filter algorithm based on a fuzzy membership function. The proposed algorithm calculates the Gaussian filter weight considering the standard deviation of the filtering mask and computes an estimate according to the fuzzy membership function. The final output is calculated by adding or subtracting the Gaussian filter output and estimate. To evaluate the proposed algorithm, simulations were conducted using existing additive white Gaussian noise removal algorithms. The proposed algorithm was then analyzed by comparing the peak signal-to-noise ratio and differential image. The simulation results show that the proposed algorithm has superior noise reduction performance and improved performance compared to the existing method.

• Korean Journal of Mathematics
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• 제31권4호
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• pp.485-494
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• 2023

The degree of hesitancy of a vertex in a hesitancy fuzzy graph depends on the degree of membership and non-membership of the vertex. We define a new class of hesitancy fuzzy graph, the intuitionistic hesitancy fuzzy graph in which the degree of hesitancy of a vertex is independent of the degree of its membership and non-membership. We introduce the idea of β-product of a pair of hesitancy fuzzy graphs and intuitionistic hesitancy fuzzy graphs and prove certain results based on this product.

• 한국음향학회지
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• 제11권3호
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• pp.40-52
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• 1992

본논문에서는 불특정화자 음성인식의 문제점이 되는 개인차에 의한 변동을 흡수하기 위하여 사상멤버쉽함수에 의한 화자적응 단어인식 방법을 제안하였다. 이방법의 학습과정에서는 미지화자의 표준화자의 스펙트럼패턴 사이에서 작성된 사상코드북에 퍼지이론을 도입하여 사상멤버쉽함수를 작성하였으며, 인식과정에서는 미지화자의 음성패턴을 사상멤버쉽함수에 의해 표준화자의 음성패턴에 적응된 패턴으로 재구성하고 뉴럴-퍼지패턴매칭에 의해 단어를 인식하였다. 본 방법의 타당성을 평가하기 위하여, 28개의 DDD 지역명을 대상으로 실험한 결과, 종래의 사상코드북에 의한 벡터양자화 화자적응방법에서는 64.9[%], 퍼지벡터양자화 화자적응방법에서는 76.1[%]의 인식율을 얻었으나, 사상멤버쉽함수에 의한 화자적응방법에서는 95.4[%]의 향상된 인식율을 얻으므로써 인식성능의 우수함을 확인하였다. 또한 사상멤버쉽함수의 작성과정에서는 반복된 학습과정이 불피요하며, 기억용량과 계산량도 사상코드북에 의한 화자적응방법보다 각각 1/30, 1/500배 정도였다.