• Korean Journal of Computational Design and Engineering
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• v.14 no.6
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• pp.382-389
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• 2009

Recently, knowledge management has been required in companies as a tool of competitiveness. Companies have constructed Enterprise Resource Planning(ERP) system in order to manage huge knowledge. But, it is not easy to formalize knowledge in organization. We focused on data mining system by genetic programming(GP). Data mining system by genetic programming can be useful tools to derive and extract the necessary information and knowledge from the huge accumulated data. However when we don't have enough amounts of data to perform the learning process of genetic programming, we have to reduce input parameter(s) or increase number of learning or training data. In this study, an enhanced data mining method combining Genetic Programming with Self organizing map, that reduces the number of input parameters, is suggested. Experiment results through a prototype implementation are also discussed.

• Computers and Concrete
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• v.23 no.4
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• pp.255-265
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• 2019

The potential of using genetic programming to predict engineering data has caught the attention of researchers in recent years. The present paper utilized weighted genetic programming (WGP), a derivative model of genetic programming (GP), to model the compressive strength of concrete. The calculation results of Abrams' laws, which are used as the design codes for calculating the compressive strength of concrete, were treated as the inputs for the genetic programming model. Therefore, knowledge of the Abrams' laws, which is not a factor of influence on common data-based learning approaches, was considered to be a potential factor affecting genetic programming models. Significant outcomes of this work include: 1) the employed design codes positively affected the prediction accuracy of modeling the compressive strength of concrete; 2) a new equation was suggested to replace the design code for predicting concrete strength; and 3) common data-based learning approaches were evolved into knowledge-based learning approaches using historical data and design codes.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2006.04a
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• pp.185-191
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• 2006

As development of information technology, companies stress the need of knowledge management. Companies construct ERP system including knowledge management. But, it is not easy to formalize knowledge in organization. They experience that constructing information system help knowledge management. Now, we focus on engineering knowledge. Because engineering data contains experts' experience and know-how in its own, engineering knowledge is a treasure house of knowledge. Korean shipyards are leader of world shipbuilding industry. They have accumulated a store of knowledges and data. But, they don't have data minning tool to utilize accumulated data. This paper treats development of data minning tools for the utilization of shipbuilding knowledge based on genetic programming (GP).

• The Journal of Korean Association of Computer Education
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• v.19 no.2
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• pp.1-10
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• 2016

This study is for developing a programming education course to improve pre-service teachers' pedagogical content knowledge(PCK) of programming education. A 40-hour training course was designed with App Inventor, a block-based mobile programming environment, and with problem-based learning method and project-based learning method. After the curriculum was adopted to 12 undergraduate students, the effect of education was tested with a programming PCK questionnaire. As a result, after a 20-hour problem-based learning class, overall score and teaching method score were enhanced significantly. After another 20-hour project-based learning class, content knowledge, teaching method, and curriculum score were improved.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.04a
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• pp.290-293
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• 2000

Knowledge discovery refers to the overall process of discovering useful knowledge from data. The linear programming model is a special form of useful knowledge that is embedded in a database. Since formulating models from scratch requires knowledge-intensive efforts, knowledge-based formulation support systems have been proposed in the DSS area. However, they rely on the strict assumption that sufficient domain knowledge should already be captured as a specific knowledge representation form. Hence, the purpose of this paper is to propose a methodology that finds useful knowledge on building linear programming models from a database. The methodology consists of two parts. The first part is to find s first-cut model based on a data dictionary. To do so, we applied the GPS algorithm. The second part is to discover a second-cut model by applying neural network technique. An illustrative example is described to show the feasibility of the proposed methodology.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.215-218
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• 1996

In work scheduling problems, scheduling constraints are not absolutely rigid; they may be changed depending on the scheduling aspect effected. In order to cope with changes in scheduling constraints and assignment strategies and to optimize scheduling results quickly, this paper will propose a new scheduling method which combines knowledge engineering and mathematical programming techniques.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.19 no.37
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• pp.171-178
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• 1996

The programmable logic controller(PLC) programming has been manually carried out, which might cause the productivity decrease by omission and repetition of instruction. Recently, the knowledge-based automatic programming system is introduced. In the system, input/output(I/O) addresses are input by user. In this study, we developed the prototype system for automatic I/O addressing using knowledge-based technology, With the developed system, the PLC addressing task can he consistently and effectively performed.

• The Journal of Korean Association of Computer Education
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• v.14 no.1
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• pp.69-79
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• 2011

In this paper I present the framework for programming education relating to the programming course in university. First of all, I identify the literature of the psychological and educational study of programming in domestic and foreign country. Some outstanding papers in foreign country show that the mental model, programming knowledge and strategies are the important difference between novice and expert programmers. And various problems experienced by novice programmers are identified. I summarise this material and suggest some practical implications for programming teachers in their teaching activity. The framework for programming education presented by this work has three dimensions of program development process, programming learning factors and teaching and learning methods for programming to develope the novice's programming skill. It helps the programming teacher to design, implement and evaluate their programming course with the guideline of programming activities.

• Journal of the Korean Operations Research and Management Science Society
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• v.25 no.3
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• pp.91-107
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• 2000

The linear programming model is a special form of useful knowledge that is embedded in a database. Since formulating models from scratch requires knowledge-intensive efforts, knowledge-based formulation support systems have been proposed in the Decision Support Systems area. However, they rely on the assumption that sufficient domain knowledge should already be captured as a specific knowledge representation form. Hence, the purpose of this paper is to propose a methodology that finds useful knowledge on building linear programming models from a database. The methodology consists of two parts. The first part is to find s first-cut model based on a data dictionary. To do so, we applied the General Problem Solver(GPS) algorithm. The second part is to discover a second-cut model by applying neural network technique. An illustrative example is described to show the feasibility of the proposed methodology.

• Journal of the Society of Naval Architects of Korea
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• v.43 no.6 s.150
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• pp.700-706
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• 2006

As development of information technology, companies stress the need of knowledge management. Companies construct ERP system including knowledge management. But, it is not easy to formalize knowledge in organization. They experience that constructing information system help knowledge management. Now, we focus on engineering knowledge. Because engineering data contains experts' experience and know-how in its own, engineering knowledge is a treasure house of knowledge. Korean shipyards are leader of world shipbuilding industry. They have accumulated a store of knowledge and data. But, they don't have data mining tool to utilize accumulated data. This paper treats development of data mining tools for the utilization of shipbuilding knowledge based on genetic programming(GP).