• Journal of the Korean Institute of Intelligent Systems
• /
• v.15 no.7
• /
• pp.800-804
• /
• 2005

This paper presents a fuzzy learning rule which is the fuzzified version of LVQ(Learning Vector Quantization). This fuzzy learning rule 3 uses fuzzy learning rates. instead of the traditional learning rates. LVQ uses the same learning rate regardless of correctness of classification. But, the new fuzzy learning rule uses the different learning rates depending on whether classification is correct or not. The new fuzzy learning rule is integrated into the improved IAFC(Integrated Adaptive Fuzzy Clustering) neural network. The improved IAFC neural network is both stable and plastic. The iris data set is used to compare the performance of the supervised IAFC neural network 3 with the performance of backprogation neural network. The results show that the supervised IAFC neural network 3 is better than backpropagation neural network.

• Journal of Digital Convergence
• /
• v.10 no.11
• /
• pp.279-285
• /
• 2012

This study classified the categorization process of convergence products as a rule-based and a similarity-based categorization process. And we examined that how the categorization process was determined according to information types(visual vs. visual + verbal) about the components of two prototypes before convergence and thinking styles(holistic vs. analytic). The result of this study showed: (1) The rule-based categorization process appeared more in case of visual information with verbal information than only visual information. (2) Analytic thinkers chose a rule-based categorization process more than holistic thinkers. These findings provide the theoretical and practical implications to comprehend the categorization process of convergence products and the judgement for consideration set from various convergence products.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.42 no.6
• /
• pp.55-62
• /
• 2005

It is essential for a fuzzy logic controller to have an appropriate set of rules to perform at the desired level. The linguistic structure of the fuzzy logic controller allows a tentative linguistic policy to be used as an initial rule base. At the design stage, if one can reasonably assemble a good collection of rules, it may then be possible to be tuned to improve the controller performance. In this paper, we proposed the shifting method of rule base table to improve the performance of fuzzy controller. The proposed method is based on the principle of that the effect of the output to regulate the system would be greater when the error increases and the effect of output would be less when the error decreases. According to simulation results, it is an effective method to improve the fuzzy control rule base and the performance of fuzzy logic controllers.

• Journal of radiological science and technology
• /
• v.43 no.2
• /
• pp.65-70
• /
• 2020

PA(postero-anterior) and AP(antero-posterior) chest projections are the most sought-after types of all kinds of projections. But if a radiological technologist puts wrong information about the position in the computer, the orientation of left and right side of an image would be reversed. In order to solve this problem, we utilized CNN(convolutional neural network) which has recently utilized a lot for studies of medical imaging technology and rule-based system. 70% of 111,622 chest images were used for training, 20% of them were used for testing and 10% of them were used for validation set in the CNN experiment. The same amount of images which were used for testing in the CNN experiment were used in rule-based system. Python 3.7 version and Tensorflow r1.14 were utilized for data environment. As a result, rule-based system had 66% accuracy on evaluating whether the orientation reversal on chest x-ray image. But the CNN had 97.9% accuracy on that. Being overcome limitations by CNN which had been shown on rule-based system and shown the high accuracy can be considered as a meaningful result. If some problems which can occur for tasks of the radiological technologist can be separated by utilizing CNN, It can contribute a lot to optimize workflow.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.64 no.4
• /
• pp.11-20
• /
• 2022

Currently, the operation rule of agricultural reservoirs in case of drought events follows the drought forecast warning standard of agricultural water supply. However, it is difficult to preemptively manage drought in individual reservoirs because drought forecasting standards are set according to average reservoir storage ratio such as 70%, 60%, 50%, and 40%. The equal standards based on average water level across the country could not reflect the actual drought situation in the region. In this study, we proposed the improvement of drought operation rule for agricultural reservoirs based on the percentile approach using past water level of each reservoir. The percentile approach is applied to monitor drought conditions and determine drought criteria in the U.S. Drought Monitoring (USDM). We applied the drought operation rule to reservoir storage rate in extreme 2017 spring drought year, the one of the most climatologically driest spring seasons over the 1961-2021 period of record. We counted frequency of each drought criteria which are existing and developed operation rules to compare drought operation rule determining the actual drought conditions during 2016-2017. As a result of comparing the current standard and the percentile standard with SPI6, the percentile standard showed severe-level when SPI6 showed severe drought condition, but the current standard fell short of the results. Results can be used to improve the drought operation criteria of drought events that better reflects the actual drought conditions in agricultural reservoirs.

• International Journal of Control, Automation, and Systems
• /
• v.4 no.6
• /
• pp.669-681
• /
• 2006

In this work, a new method of design adaptive controllers for SISO systems based on multiple models and switching is presented. The controller selects the model from a given set, according to a switching rule based on output prediction errors. The goal is to design, at each sample instant, a predictive control law that ensures the robust stability of the closed-loop system and achieves the best performance for the current operating point. At each sample the proposed control scheme identifies a set of linear models that best characterizes the dynamics of the current operating region. Then, it carries out an automatic reconfiguration of the controller to achieve the best possible performance whilst providing a guarantee of robust closed-loop stability. The results are illustrated by simulations a nonlinear continuous and stirred tank reactor.

• Journal of Electrical Engineering and Technology
• /
• v.12 no.1
• /
• pp.72-77
• /
• 2017

This paper proposes the explicit tuning rule of multi-loop PID controller for brushless direct current motors to predict the system behaviors in time and frequency domains, using properties of the convex combination method. The convex set of the proposed controllers formulates the envelope to satisfy the performances in time and frequency domains. The final control parameters are determined by solving the convex optimization problem subject to the constraints which are represented as convex set of time domain performances. The effectiveness of the proposed control method is shown in the numerical simulation, in which controller tuning algorithm and dynamics of brushless DC motor are well taken into account.

• MALSORI
• /
• v.68
• /
• pp.75-93
• /
• 2008

An example-based dialogue system tries to utilize many pairs which are stored in a dialogue database. The most important part of the example-based dialogue system is to find the most similar utterance to user's input utterance. Modality, which is characterized as conveying the speaker's involvement in the propositional content of a given utterance, is one of the core sentence features. For example, the sentence "I want to go to school." has a modality of hope. In this paper, we have proposed a modality classification system which can predict sentence modality in order to improve the performance of example-based dialogue systems. We also define a modality tag set for a dialogue system, and validate this tag set using a rule-based modality classification system. Experimental results show that our modality tag set and modality classification system improve the performance of an example-based dialogue system.

• The KIPS Transactions:PartB
• /
• v.9B no.6
• /
• pp.783-790
• /
• 2002

This paper proposes a fuzzy Pr/T net representation of interval-valued fuzzy set reasoning, where fuzzy production rules are used for knowledge representation, and the belief of fuzzy production rules are represented by interval-valued fuzzy sets. The presented interval-valued fuzzy reasoning algorithm is much closer to human intuition and reasoning than other methods because this algorithm uses the proper belief evaluation functions according to fuzzy concepts in fuzzy production rules.

• Journal of applied mathematics & informatics
• /
• v.35 no.5_6
• /
• pp.565-586
• /
• 2017

In this paper we continue to investigate the Super Vertex Mean behaviour of all graphs up to order 5 and all regular graphs up to order 7. Let G(V,E) be a graph with p vertices and q edges. Let f be an injection from E to the set {1,2,3,${\cdots}$,p+q} that induces for each vertex v the label defined by the rule $f^v(v)=Round\;\left({\frac{{\Sigma}_{e{\in}E_v}\;f(e)}{d(v)}}\right)$, where $E_v$ denotes the set of edges in G that are incident at the vertex v, such that the set of all edge labels and the induced vertex labels is {1,2,3,${\cdots}$,p+q}. Such an injective function f is called a super vertex mean labeling of a graph G and G is called a Super Vertex Mean Graph.