• Journal of the Korean Mathematical Society
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• v.43 no.1
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• pp.11-28
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• 2006

The existence, uniqueness and iterative approximation of solutions for a few classes of functional equations arising in dynamic programming of multistage decision processes are discussed. The results presented in this paper extend, improve and unify the results due to Bellman [2, 3], Bhakta-Choudhury [6], Bhakta-Mitra [7], and Liu [12].

• The Pure and Applied Mathematics
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• v.18 no.4
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• pp.345-351
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• 2011

Taylor's formula is a powerful tool in analysis. In this study, we assume that an operator is m-times Fr$\acute{e}$chet-differentiable and satisfies a Lipschitz condition. We then obtain some Taylor formulas using only the Lipschitz constants. Applications are also provided.

• International Journal of Control, Automation, and Systems
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• v.1 no.3
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• pp.358-367
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• 2003

We consider discrete-time factorial Markov Decision Processes (MDPs) in multiple decision-makers environment for infinite horizon average reward criterion with a general joint reward structure but a factorial joint state transition structure. We introduce the "localization" concept that a global MDP is localized for each agent such that each agent needs to consider a local MDP defined only with its own state and action spaces. Based on that, we present a gradient-ascent like iterative distributed algorithm that converges to a local optimal solution of the global MDP. The solution is an autonomous joint policy in that each agent's decision is based on only its local state.cal state.

• International Journal of Quality Innovation
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• v.8 no.2
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• pp.115-131
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• 2007

The vehicle development process (VDP) is iterative in nature with numerous interactions and information flows between design groups and between development phases. The VDP has been changed from a sequential-functional development to a concurrent-team based approach. Concurrent execution of design activities may reduce the development lead-time, but it increases the managerial complexity in the VDP. A system dynamics model was developed to understand the transient behavior of parallel, overlap, and sequential processes in the VDP and to determine the optimal level of overlapping considering the development lead-time and total number of reworks. The simulation results showed that different execution processes should be used, depending upon the intensity of reworks.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.5 s.176
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• pp.1133-1145
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• 2000

It is necessary to develop an efficient analysis method to identify the dynamic characteristics of a large mechanical structure and update its finite element model. That is because these processes need the huge computation of a large structure and iterative estimation due to the use of the first- order sensitivity. To efficiently carry out these processes, a new method, called the generalized free-interface mode sensitivity method, has been proposed in the authors' preceeding paper. This method is based on substructuring approach such as a free-interface method and a generalized synthesis algorithm. In this paper, the proposed method is applied to the model updating of a car body structure to verify its accuracy and reliability for a large mechanical structure.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.248-251
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• 1999

The optimal reaction conditions are determined for a PET process, which consists of transesteriflcation, prepolymerization and polycondensation reactors in series. Based on the simulation results of the reactor system, we scrutinize the cause and effect between the reaction conditions and the final properties of the polymer product. We then select the process variables with significant influence on the properties of polymer as control variables and calculate the optimal reaction conditions by iterative dynamic programming (IDP) algorithm with constraints. A new reaction scheme incorporating reactions for by-products as well as three main reactions is considered in the constrained IDP method.

• Economic and Environmental Geology
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• v.28 no.4
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• pp.425-431
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• 1995

Genetic algorithms are so named because they are analogous to biological processes. The model parameters are coded in binary form. The algorithm then starts with a randomly chosen population of models called chromosomes. The second step is to evaluate the fitness values of these models, measured by a correlation between data and synthetic for a particular model. Then, the three genetic processes of selection, crossover, and mutation are performed upon the model in sequence. Genetic algorithms share the favorable characteristics of random Monte Carlo over local optimization methods in that they do not require linearizing assumptions nor the calculation of partial derivatives, are independent of the misfit criterion, and avoid numerical instabilities associated with matrix inversion. An additional advantage over converntional methods such as iterative least squares is that the sampling is global, rather than local, thereby reducing the tendency to become entrapped in local minima and avoiding the dependency on an assumed starting model.

• Transactions of Materials Processing
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• v.16 no.1 s.91
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• pp.15-19
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• 2007

This paper presents an integrated machining error compensation method based on captured images of tool deflection shapes in flat end-milling processes. This approach allows us to avoid modeling machining characteristics (cutting forces, tool deflections and machining errors etc.) and accumulating calculation errors induced by several simulations. For this, a high-speed camera captured images of real deformed tool shapes which were cutting under given machining conditions. Using image processes and a machining error model, it is possible to estimate tool deflection in cutting conditions modeled and to compensate for machining errors using an iterative algorithm correcting tool paths. This corrected tool path can effectively reduce machining errors in the flat end-milling process. Experiments are carried out to validate the approaches proposed in this paper. The proposed error compensation method can be effectively implemented in a real machining situation, producing much smaller errors.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 1997.10a
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• pp.164-167
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• 1997

The die wear is one of the main factors affecting die accuracy and tool lifetime. It is desired to reduce die wear by developing simulation method to predict wear based on process parameters, and then optimize the process. Therefore, this paper describes disign methodology of preform for minimizing wear of finisher die in multi-stage cold forging processes. The finite element method is combined with the routine of wear prediction and the cold forging processes. The finite element method is combined with the routine of wear prediction and the cold forging process is analyzed. In order to obtain preform to minimize die wear, the FPS algorithm is applied and the optimal preform shape is found from iterative deformation analysis and wear calculation.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.14 no.2
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• pp.9-16
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• 2006

FAA AC120-40B Level D flight dynamics model for T-50 Full Mission Trainer was successfully developed. Since AC120-40B Level D requires the quantitative validation tests for simulation model compared with flight test data, T-50 flight test data for each validation test item was gathered, and also automatic test environments which include AFT (Automatic Fidelity Tester) and STA (Simulation Test Analyzer) were developed. The final test results after the iterative test-tuning processes were all within the tolerances specified in AC120-40B Level D. Qualification Test Guide, QTG contains the detail test processes and results.