• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.4
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• pp.333-338
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• 2005

This paper presents the target object search algorithm under Dynamic Programming (DP) in the Tree-type maze. We organized an experimental environment with the concatenation of Y-shape diverged way, small mobile robot, and a target object. By the principle of optimality, the backbone of DP, an agent recognizes that a given whole problem can be solved whether the values of the best solution of certain ancillary problem can be determined according to the principle of optimality. In experiment, we used two different control algorithms: a left-handed method and DP. Finally we verified the efficiency of DP in the practical application using our real robot.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.29 no.11
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• pp.592-604
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• 2017

A chiller, having a thermal storage system, can contribute to load-leveling and can reduce the cost of electricity by using electricity at night. In this study, the control experiments and simulations are conducted using both conventional and advanced methods for the building cooling system. Advanced approaches, such as the "region control method", divide the control region into five zones according to the size of the building load, and determines the cooling capacities of the chiller and thermal storage. On the other hand, the "dynamic programming method" obtains the optimal cooling capacities of the chiller and thermal storage by selecting the minimum-cost path by carrying out repetitive calculations. The "thermal storage priority method" shows an inferior chiller performance owing to the low-part load operation, whereas the chiller priority method leads to a high electric cost owing to the low utilization of thermal storage and electricity at night. It has been proven that the advanced control methods have advantages over the conventional methods in terms of electricity consumption, as well as cost-effectiveness. According to the simulation results during the winter season, the electric cost when using the dynamic programming method was 6.5% and 8.9% lower than that of the chiller priority and the thermal storage priority methods, respectively. It is therefore concluded that the cost of electricity utilizing the region control method is comparable to that of the dynamic programming method.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2617-2622
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• 2003

The pH neutralization process has long been taken as a representative benchmark problem of nonlinear chemical process control due to its nonlinearity and time-varying nature. For general nonlinear processes, it is difficult to control with a linear model-based control method so nonlinear controls must be considered. Among the numerous approaches suggested, the most rigorous approach is the dynamic optimization. However, as the size of the problem grows, the dynamic programming approach is suffered from the curse of dimensionality. In order to avoid this problem, the Neuro-Dynamic Programming (NDP) approach was proposed by Bertsekas and Tsitsiklis (1996). The NDP approach is to utilize all the data collected to generate an approximation of optimal cost-to-go function which was used to find the optimal input movement in real time control. The approximation could be any type of function such as polynomials, neural networks and etc. In this study, an algorithm using NDP approach was applied to a pH neutralization process to investigate the feasibility of the NDP algorithm and to deepen the understanding of the basic characteristics of this algorithm. As the global approximator, the neural network which requires training and k-nearest neighbor method which requires querying instead of training are investigated. The global approximator requires optimal control strategy. If the optimal control strategy is not available, suboptimal control strategy can be used even though the laborious Bellman iterations are necessary. For pH neutralization process it is rather easy to devise an optimal control strategy. Thus, we used an optimal control strategy and did not perform the Bellman iteration. Also, the effects of constraints on control moves are studied. From the simulations, the NDP method outperforms the conventional PID control.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.6
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• pp.11-20
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• 1997

This paper proposes a modified dynamic programming for finding the correspondence between right and left images. A dynamic programming is based on the intensity of images for stereo matching. But htis method is intended to mismatch at uniformed intensity region. To reduce thd mismatching, the stereo images are segmented to various regions with respective uniform intensity, and the different cost function has applied to the segmented region during the dynamci programming. Cost function costains jump cost. And jump cost included two parameter .alpha. and .beta. which have influence on minimum cost path. Experimental results show that the 3D shape of some stereo pairs cna be finely obtained by this proposed algorithm.

• Journal of Korean Association for Spatial Structures
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• v.12 no.2
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• pp.89-98
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• 2012

This study investigates the optimum structural design of space truss considering global buckling, and is to obtain the minimal weight of the structure. The mathematical programming method is used for optimization of each member by member force. Besides, dynamic programming method is adapted for consideration in snap-through buckling. The mathematical modeling for optimum design of truss members consists of objective function of total weight and constrain equations of allowable tensile (or compressive) stress and slenderness. The tangential stiffness matrix is examined to find the critical point on equilibrium path, and a ratio of the buckling load to design load is reflected in iteration procedures of dynamic programming method to adjust the stiffness of space truss. The star dome is examined to verify the proposed optimum design processor. The numerical results of the model are conversed well and satisfied all constrains. This processor is a relatively simple method to carry out optimum design with consideration in global buckling, and is viable in practice with respect to structural design.

• Journal of the Chungcheong Mathematical Society
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• v.29 no.2
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• pp.375-383
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• 2016

This paper investigates an optimal consumption, portfolio, and life insurance strategies of a family when there is a borrowing constraint and risk aversion change at the time of death of the breadwinner. A CRRA utility is employed and by using the dynamic programming method, we obtain analytic expressions for the optimal strategies.

• IE interfaces
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• v.12 no.3
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• pp.362-373
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• 1999

Resource Constrained Dynamic Multi-Projects Scheduling (RCDMPS) is intended to schedule activities of two or more projects sequentially arriving at die shop under restricted resources. The aim of this paper is to develop a new problem solving method for RCDMPS to make an effect schedule based by constraint programming. The constraint-based scheduling method employs ILOG Solver which is C++ constraint reasoning library for solving complex resource management problems and ILOG Schedule which is a add-on library to ILOG Solver dedicated to solving scheduling problems. And this method interfaces with ILOG Views so that the result of scheduling displays with Gantt chart. The scheduling method suggested in this paper was applied to a company scheduling problem and compared with the other heuristic methods, and then it shows that the new scheduling system has more preference.

• Journal of the Korea Society for Simulation
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• v.16 no.1
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• pp.21-29
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• 2007

In this paper, we present a method of detecting the boundary of the intima-media complex for automated measurement based on dynamic programming from carotid artery B-mode ultrasound images and then show the experimental results. We apply the dynamic programming for determining the optimal locations that a cost function is minimized. The cost function includes cost terms which are representing image features such as intensity, intensity gradient and geometrical continuity of the vessel interfaces. Moreover, we improve the boundary continuity by applying the B-spline to smooth the rough boundary due to noise such as speckle, dropout and weak edges. The proposed method has obtained more accurate reproducible results than conventional edge-detection by considering multiple image features and ensures efficient automated measurement by solving the problems of the inter- and intra-observer variability and its inefficiency due to manual measurement.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.9
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• pp.540-546
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• 2003

A fast pattern classification algorithm with Cellular Nonlinear Network-based dynamic programming is proposed. The Cellular Nonlinear Networks is an analog parallel processing architecture and the dynamic programing is an efficient computation algorithm for optimization problem. Combining merits of these two technologies, fast pattern classification with optimization is formed. On such CNN-based dynamic programming, if exemplars and test patterns are presented as the goals and the start positions, respectively, the optimal paths from test patterns to their closest exemplars are found. Such paths are utilized as aggregating keys for the classification. The algorithm is similar to the conventional neural network-based method in the use of the exemplar patterns but quite different in the use of the most likely path finding of the dynamic programming. The pattern classification is performed well regardless of degree of the nonlinearity in class borders.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.451-452
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• 2007

In this paper, we simulate power system transient stability using object-oriented programming(OOP). OOP is a more flexible method than procedual programming. There are several advantages in dynamic system simulation using OOP. We also calculate critical fault clearing time using energy functions for detailed models.