• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1993.06a
• /
• pp.899-902
• /
• 1993

A neural model predictive control strategy combining a neural network for plant identification and a nonlinear programming algorithm for solving nonlinear control problems is proposed. A constrained nonlinear optimization approach using successive quadratic programming combined with neural identification network is used to generate the optimum control law for complex continuous chemical reactor systems that have inherent nonlinear dynamics. The neural model predictive controller (MNPC) shows good performances and robustness. To whom all correspondence should be addressed.

• The Journal of Korean Association of Computer Education
• /
• v.15 no.6
• /
• pp.1-10
• /
• 2012

It is reported that programming education contributes to improving problem solving skills by developing higher thinking skills. As many researches mention the need of programming education, they point to the fundamental difference by gender. This study aims to find out the cause of low interest and achievement levels in programming education in female students. To achieve our goals, we chose 133 specialized high school students in which programming class is being carried out as subjects of our study. The results of this study showed that female students had the tendency to prefer individual projects to a more systematic method of problem solving. Moreover, according to correlation analysis, higher programming skills in female students showed various problem solving processes. This study shows significance in proposing different study methods according to gender to obtain effective programming study.

• The Journal of Korean Association of Computer Education
• /
• v.17 no.4
• /
• pp.13-21
• /
• 2014

Recently, domestically and abroad, programming education has become more important and this increase has been recognized. And it needs a certain criteria for a selection of programming tools because there are various educational programming tools coming out. Thus, we tried to develop a criteria on the selection of educational programming language for a novice programmer and K12 students and verify its validity. So we established 4 areas and 28 items for selection criteria on educational programming language. Additionally, we carried out delphi survey and analyze for validity verification on selection criteria established. As result of carrying out of these processes, we developed 4 areas of selection criteria. Finally we have chosen 19 selection criteria and excluded 9 criteria items which are not sufficient with validity criteria through delphi survey.

• The Transactions of the Korea Information Processing Society
• /
• v.6 no.2
• /
• pp.485-496
• /
• 1999

Comparing with sequential programming, parallel programming has additional complexity due to the consideration of parallelism, communication and synchronization of processes. A synergism between users and compliers should be established, each assisting the other to produce high quality parallel programs. On the above underlying philosophy, we developed a parallel Object-Oriented specification language, POOSL, as preliminary works. However, it is still likely to hard for users to write parallel program because users have to consider grammar of POOSL and to write text-based parallel program. It would be more desirable to provide users wit visual environment for effective parallel programming. Therefore, we propose a visual programming environment. VEPO(Visual environment for Parallel Object-Oriented Programming), based on POOSL in order that users can develop parallel programs more easily and conveniently. It aims at supporting a programming environment in which users can represent their programs more naturally and visually I parallel manner with object-oriented concept and essential steps during parallel program development such as program specification, compilation, execution and animation of execution are integrated. VEPO has useful features for parallel processing. Especially, complicated parallel codes for synchronization and communication of processes are automatically generated in the translation phase, so users can be relieved of writing error-prone parallel codes. The system is targeted to the transputer-based parallel system, MC-3. The graphic user interface of VEPO was implemented using Visual C++. Visual programs descirbed on VEPO are translated into Inmos C and executed on MC-3.

• 제어로봇시스템학회:학술대회논문집
• /
• 2001.10a
• /
• pp.163.3-163
• /
• 2001

This paper presents the two-step strategy method of performing optimal scheduling of paper mill processes using MINLP (Mixed-Integer Non-Linear Programming) considering the trim loss problem in sheet cutting processes. The mathematical model for a sheet cutting process in the form of MINLP is developed in this study, and minimizing total cost is performed considering the cost of raw paper roll, :hanging cutting patterns, storage of over-product and recycling/burning trim. The paper has been used to deliver and conserve information for a long time, and it is needed to have various sizes and weights ...

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1993.06a
• /
• pp.1346-1349
• /
• 1993

In this paper, we describe the use of certain optimization techniques, principally dynamic programming and high level computational methods, to enhance the capabilities of a fuzzy adaptive neural network controller which we had developed for on-line control and adaption on complex nonlinear processes. Potential applications to an array of processes from diverse fields are discussed.

• 제어로봇시스템학회:학술대회논문집
• /
• 2004.08a
• /
• pp.1870-1873
• /
• 2004

The objective of this study is to investigate the possibility of chemical process synthesis purely based on mathematical programming when given an objective, feed conditions, product specifications, and model equations for available process units. A method based on a state space approach is proposed, and applied to an example problem with a reactor, a heat exchanger, and a separator. The results indicate that a computer can automatically synthesize an optimal process without any heuristics or expertise in process design provided that global optimization techniques are improved to be suitable for large problems.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.41 no.3
• /
• pp.121-127
• /
• 2004

This paper presents a new vertex selection scheme for shape approximation. In the proposed method, final vertex points are determined by "two-step procedure". In the first step, initial vertices are simply selected on the contour, which constitute a subset of the original contour, using conventional methods such as an iterated refinement method (IRM) or a progressive vertex selection (PVS) method In the second step, a vertex adjustment Process is incorporated to generate final vertices which are no more confined to the contour and optimal in the view of the given distortion measure. For the optimality of the final vertices, the dynamic programming (DP)-based solution for the adjustment of vertices is proposed. There are two main contributions of this work First, we show that DP can be successfully applied to vertex adjustment. Second, by using DP, the global optimality in the vertex selection can be achieved without iterative processes. Experimental results are presented to show the superiority of our method over the traditional methods.

• Proceedings of the Korea Inteligent Information System Society Conference
• /
• 2004.11a
• /
• pp.171-178
• /
• 2004

This study suggests a general paradigm enhancing genetic mutability. Mutability among heterogeneous members in a genetic population has been a major problem in application of genetic programming to diverse business problems. This suggested paradigm is implemented to developing new methods from existing methods. Within the evolutionary approach taken to designing new methods, a general representation scheme of the genetic programming framework, called a kernel, is introduced. The kernel is derived from the literature of algorithms and heuristics for combinatorial optimization problems. The commonality and differences among these methods have been identified and again combined by following the genetic inheritance merging them. The kernel was tested for selected methods in combinatorial optimization. It not only duplicates the methods in the literature, it also confirms that each of the possible solutions from the genetic mutation is in a valid form, a running program. This evolutionary method suggests diverse hybrid methods in the form of complete programs through evolutionary processes. It finally summarizes its findings from genetic simulation with insight.

• Journal of information and communication convergence engineering
• /
• v.6 no.4
• /
• pp.448-453
• /
• 2008

This study describes design and development techniques of estimation models for process modeling. One case study is undertaken to design a model using standard gas furnace data. Neural networks (NN) and genetic programming (GP) are each employed to model the crucial relationships between input factors and output responses. In the case study, two models were generated by using 70% training data and evaluated by using 30% testing data for genetic programming and neural network modeling. The model performance was compared by using RMSE values, which were calculated based on the model outputs. The average RMSE for training and testing were 0.8925 (training) and 0.9951 (testing) for the NN model, and 0.707227 (training) and 0.673150 (testing) for the GP model, respectively. As concern the results, the NN model has a strong advantage in model training (using the all data for training), and the GP model appears to have an advantage in model testing (using the separated data for training and testing). The performance reproducibility of the GP model is good, so this approach appears suitable for modeling physical fabrication processes.