• IEMEK Journal of Embedded Systems and Applications
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• v.13 no.4
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• pp.179-185
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• 2018

Particulate Matter (PM2.5) has various adverse effects on health. Climate and industry activity and traffic volume are the main causes, especially in urban area. In order to construct an effective forecasting system, many measurement systems are required, but it is impossible in reality. Therefore, in this study, we propose a method to infer PM2.5 condition by using rule induction technique. The experimental results showed a classification accuracy of 71%.

• Journal of Educational Research in Mathematics
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• v.12 no.2
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• pp.275-290
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• 2002

This Study takes Peirce' abduction which is Phenomenology' first reasoning mode, as a part of mathematical reasoning with deduction and induction. Abduction(retroduction, hypothesis, presumption, and originary argument) leads a case through a result and a rule, while deduction leads a result through a rule and a case and induction leads a rule through a case and a result. Polya(1954) involved generalization, specialization, and analogy within induction, but this paper contain analogy in abduction. And metaphors and metonymies are also contained in abduction, in which metaphors are contained in analogy. Metaphors and metonymies are applied to semiosis i.e. the signification of mathematical signs. Semiotic analysis for a student's problem solving showed the semiosis with metaphors and metonimies. Thus, abductions should be regarded as a mathematical reasoning, and we must utilize abductions in mathematical teaming since abductions are thought as a natural reasoning by students.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.1
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• pp.44-51
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• 2003

Knowledge acquisition is a bottleneck in knowledge-based system implementation. Decision tree induction is a useful machine learning approach for extracting classification knowledge from a set of training examples. Many real-world data contain fuzziness due to observation error, uncertainty, subjective judgement, and so on. To cope with this problem of real-world data, there have been some works on fuzzy classification rule learning. This paper makes a survey for the kinds of fuzzy classification rules. In addition, it presents a fuzzy classification rule learning method based on decision tree induction, and shows some experiment results for the method.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10a
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• pp.193-195
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• 2004

기존의 규칙 귀납법(Rule Induction)은 양성적 추론(positive reasoning)과 음성적 추론(negative reasoning)을 잘 반영하지 못하고 있지만 의학 분야의 추론은 양성적 추론과 음성적 추론을 모두 포함하고 있다. 이것이 의학 전문가들이 귀납된 규칙을 해석하는데 어려움을 가지게 되며, 진단 과정을 위해서 규칙을 해석하는 것을 쉽게 진행할 수 없는 이유이기도 하다. 본 연구에서는 양성적 규칙들과 음성적 규칙들의 귀납법을 위한 두 가지 알고리즘을 적용한 진단 시스템인 DS-ARI(Diagnosis System using Algorithms for Rule Induction)물 제안한다. 제안하는 시스템과 기존 시스템을 비교해 보았을 때 제안하는 시스템에서 전문가의 지식을 보다 정확하게 표현하여 정확성을 높이게 되었다.

• Transactions of the Korean Society of Automotive Engineers
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• v.6 no.4
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• pp.66-75
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• 1998

In many case of optimal design and sensitivity analysis, obtaining of transfer function between input and output variables is a difficult and time-consuming problem. The bond graph modeling is a method that is used for making it easy to analyze complex systems composed of mechanical and electrical parts. It gives us a simple and systematic tool to get state-space equations easily. And we can obtain the transfer function graphically using bond graph and Mason's rule. This paper shows how bond graphs are converted to block diagram and how Mason's rule is applied. And the simple direct method to obtain transfer function from bond graph is introduced. As a example, induction of transfer function of electric power steering composed of mechanical and electrical parts will be done.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.10a
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• pp.395-398
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• 2004

It is effective and desirable for a proper customer relational management(CRM) to send an email of product sales' advertisement bills for the prospective customers rather than to send spam mails for non specific customers. This study identifies the prospective customers with high probability to buy the specific products using Artificial Neural Network(ANN) and Induction Rule(IR) technique. We suggest an integrated model, IRANN of ANN and IR of decision tree program C5.0 and, also compare and analyze the accuracy of ANN, IR, and IRANN each other.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1994.10a
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• pp.357-358
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• 1994

• Journal of Families and Better Life
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• v.18 no.1
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• pp.115-126
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• 2000

The purpose of hisstudy was to explore effects of adolescents age sex and parental types on the types guilty and correlations between the Rule violation types and guilty types. A All of 698 middle school students and high school students in Pusan were administered Questionaires. The major findings of this study were as follows: Younger adolescents reported more guilty feelings than older adolescents in all types of guilty. Female adolescents reported more in selfish type guilty than males. Parental induction induced adolescents reported lower rates of violation in all types of rule violation than older adolescents. Male adolescents reported more violation in public related rule violation and property damage rule violation than females. There were negative relation between all guilty types and all Rule violation, These results were discussed and its implication and following study were suggested.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.431-434
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• 2001

Knowledge discovery in databases(KDD) is the process for extracting valid, novel, potentially useful and understandable knowledge form real data. There are many academic and industrial activities with new technologies and application areas. Particularly, data mining is the core step in the KDD process, consisting of many algorithms to perform clustering, pattern recognition and rule induction functions. The main goal of these algorithms is prediction and description. Prediction means the assessment of unknown variables. Description is concerned with providing understandable results in a compatible format to human users. We introduce an efficient data mining algorithm considering predictive and descriptive capability. Reasonable pattern is derived from real world data by a revised neural network model and a proposed fuzzy rule extraction technique is applied to obtain understandable knowledge. The proposed neural network model is a hierarchical self-organizing system. The rule base is compatible to decision makers perception because the generated fuzzy rule set reflects the human information process. Results from real world application are analyzed to evaluate the system\`s performance.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1995.10b
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• pp.180-185
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• 1995

In this paper, we designed the speed controller with high accuracy and speedy steady-state response, in Induction motor control system, Fuzzy P-1 controller of Induction motor using Microprocessor have an appropriate fuzzy rule matrix (which is 2-separate Look-up Table) The usefulness of proposed fuzzy P-1 controller will be confirmed by experiments which we compare with conventional P-1 controller.