• Journal of the Korean Data and Information Science Society
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• 제25권6호
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• pp.1345-1352
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• 2014

데이터마이닝 기법 중에서 연관성 규칙은 연관성 평가 기준을 기반으로 하여 데이터베이스에 포함되어 있는 항목들 간의 관련성을 탐색하는 기법이다. 일반적인 연관성 규칙 기법과는 달리 역의 연관성 규칙은 하나의 항목집합이 발생하지 않으면 다른 항목집합도 발생하지 않는다는 규칙을 찾아내는 것이다. 이러한 역의 연관성 규칙을 일반적인 연관성 규칙과 함께 생성하면 기업체에서 특정 제품을 판매하기 위해서는 그 제품만의 마케팅뿐만 아니라 더 나아가 어떤 제품의 마케팅이 필요한 지에 대한 정보를 파악할 수 있다. 이를 위해 본 논문에서는 이러한 두 종류의 연관성 규칙에 적용 가능한 균형화된 기여 상대적 규칙 정확도를 연관성 평가 기준으로 제안하고자 한다. 또한 Piatetsky-Shapiro (1991)가 제안한 흥미도 측도가 가져야 할 조건들을 점검한 후, 예제를 통하여 제안된 측도와 연관성 규칙에 적용 가능한 의학진단분야의 평가 측도들의 유용성을 비교하였다. 그 결과, 기여 상대적 정확도와 역의 기여 상대적 정확도의 크기가 다르게 나타나면 연관성의 정도를 명확하게 설명하기가 어려우므로 이들 두 측도를 동시에 고려한 균형화된 기여 상대적 규칙 정확도를 이용하는 것이 가장 바람직하다는 사실을 확인하였다.

• International journal of advanced smart convergence
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• 제6권3호
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• pp.17-21
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• 2017

In this paper, the service execution accuracy was compared by ontology based rule inference method and machine learning method, and the amount of data at the point when the service execution accuracy of the machine learning method becomes equal to the service execution accuracy of the rule inference was found. The rule inference, which measures service execution accuracy and service execution accuracy using accumulated data and pattern matching on service results. And then machine learning method measures service execution accuracy using cross validation data. After creating a confusion matrix and measuring the accuracy of each service execution, the inference algorithm can be selected from the results.

• 대한기계학회논문집A
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• 제21권10호
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• pp.1712-1717
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• 1997

Stability and accuracy for the trapezoidal rule of the Newmark time integration method are analyzed when variable time step sizes are adopted. A new analytic approach to stability and accuracy analysis is also proposed for time integration methods with variable time step sizes. The trapezoidal rule with variable time step sizes has the "actual" unconditional stability which is the same as that of the method with constant time step sizes. However, the method with variable time step sizes is first-order accurate while the method with constant time step sizes is second-order accurate. accurate.

• 한국측량학회지
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• 제31권6_2호
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• pp.521-527
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• 2013

Rule set is an important step which impacts significantly on accuracy of object-oriented classification result. Therefore, this paper proposes a rule set to extract land cover from Landsat Thematic Mapper (TM) imagery acquired in Donganh, Hanoi, Vietnam. The rules were generated to distinguish five classes, namely river, pond, residential areas, vegetation and paddy. These classes were classified not only based on spectral characteristics of features, but also indices of water, soil, vegetation, and urban. The study selected five indices, including largest difference index max.diff; length/width; hue, saturation and intensity (HSI); normalized difference vegetation index (NDVI) and ratio vegetation index (RVI) based on membership functions of objects. Overall accuracy of classification result is 0.84% as the rule set is used in classification process.

• International Journal of Control, Automation, and Systems
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• 제5권3호
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• pp.329-336
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• 2007

This paper considers a fault accommodation problem for inertial navigation systems (INS) that have redundant inertial sensors such as gyroscopes and accelerometers. It is wellknown that the more sensors are used, the smaller the navigation error of INS is, which means that the error covariance of the position estimate becomes less. Thus, when it is decided that double faults occur in the inertial sensors due to fault detection and isolation (FDI), it is necessary to decide whether the faulty sensors should be excluded or not. A new accommodation rule for double faults is proposed based on the error covariance of triad-solution of redundant inertial sensors, which is related to the navigation accuracy of INS. The proposed accommodation rule provides decision rules to determine which sensors should be excluded among faulty sensors. Monte Carlo simulation is performed for dodecahedron configuration, in which case the proposed accommodation rule can be drawn in the decision space of the two-dimensional Cartesian coordinate system.

• 대한원격탐사학회지
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• 제27권6호
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• pp.637-651
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• 2011

This study presents a rule-based urban image classification method for time series analysis of changes in the vicinity of Asan-si and Cheonan-si in Chungcheongnam-do, using Landsat satellite images (1991-2006). The area has been highly developed through the relocation of industrial facilities, land development, construction of a high-speed railroad, and an extension of the subway. To determine the yearly changing pattern of the urban area, eleven classes were made depending on the trend of development. An algorithm was generalized for the rules to be applied as an unsupervised classification, without the need of training area. The analysis results show that the urban zone of the research area has increased by about 1.53 times, and each correlation graph confirmed the distribution of the Built Up Index (BUI) values for each class. To evaluate the rule-based classification, coverage and accuracy were assessed. When Optimal allowable factor=0.36, the coverage of the rule was 98.4%, and for the test using ground data from 1991 to 2006, overall accuracy was 99.49%. It was confirmed that the method suggested to determine the maximum allowable factor correlates to the accuracy test results using ground data. Among the multiple images, available data was used as best as possible and classification accuracy could be improved since optimal classification to suit objectives was possible. The rule-based urban image classification method is expected to be applied to time series image analyses such as thematic mapping for urban development, urban development, and monitoring of environmental changes.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 1997년도 춘계학술대회논문집; 경주코오롱호텔; 22-23 May 1997
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• pp.110-115
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• 1997

In this work, the constant average acceleration, which is a fundamental feature of the trapezoidal rule, is investigated and generalized. Using the generalization of average acceleration concept, a higher order accurate and unconditionally stable time-integration method is developed. The linear approximate of the present methods is exactly the same as the famous trapezoidal rule. To observe the accuracy and stability of the method, several numerical tests are performed and the results are compared with the results from the trapezoidal rule and the exact solution. From the numerical tests, it has been known that the present method has a higher order accuracy and unconditional stability.

• 대한방사선기술학회지:방사선기술과학
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• 제43권2호
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• pp.65-70
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• 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.

• 한국정보처리학회논문지
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• 제7권5호
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• pp.1434-1445
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• 2000

An expert system executes the inference, based on the knowledge of specific domain. the reliability on the results of inference depends upon both the consistency and accuracy of knowledge. This is the reason why expert system requires the facilities which can practice an access to the various kinds of knowledge and maintain the consistency and accuracy of knowledge an maintain the consistency and accuracy of knowledge. This paper is to implement an expert system permitting an access of declarative and procedural knowledge in the knowledge base and in the data base. This paper is also to implement a knowledge acquisition system which adds the knowledge a only if its accuracy and consistency are maintained, after verifying the potential errors such as contradiction, redundancy, circulation, non-reachable rule and non-lined rule. In consequence, the expert system realizes a good access to the various sorts of knowledge and increases the reliability on the results of inference. The knowledge acquisition system contributes tro strengthening man-machine interface that enables users to add the knowledge easily to the knowledge base.

• Journal of the Korean Statistical Society
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• 제24권2호
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• pp.453-470
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• 1995

We describe a constrained optimal classification rule for the case when the prior probability of an observation belonging to one of the two populations is unknown. This is done by suggesting a balanced design for the classification experiment and constructing the optimal rule under the balanced design condition. The rule si characterized by a constrained minimization of total risk of misclassification; the constraint of the rule is constructed by the process of equation between Kullback-Leibler's directed divergence measures obtained from the two population conditional densities. The efficacy of the suggested rule is examined through two-group normal classification. This indicates that, in case little is known about the relative population sizes, dramatic gains in accuracy of classification result can be achieved.