• International Journal of Fuzzy Logic and Intelligent Systems
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• v.11 no.3
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• pp.178-183
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• 2011

The deterministic annealing-based clustering algorithm is an EM-based algorithm which behaves like simulated annealing method, yet less sensitive to the initialization of parameters. Pairwise clustering is a kind of clustering technique to perform clustering with inter-entity distance information but not enforcing to have detailed attribute information. The pairwise deterministic annealing-based clustering algorithm repeatedly alternates the steps of estimation of mean-fields and the update of membership degrees of data objects to clusters until termination condition holds. Lacking of attribute value information, pairwise clustering algorithms do not explicitly determine the centroids or medoids of clusters in the course of clustering process or at the end of the process. This paper proposes a method to identify the medoids as the centers of formed clusters for the pairwise deterministic annealing-based clustering algorithm. Experimental results show that the proposed method locate meaningful medoids.

• Geomechanics and Engineering
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• v.23 no.1
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• pp.15-30
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• 2020

The probabilistic bearing capacity of a strip footing placed on the edge of a purely cohesive reinforced soil slope is computed by combining lower bound finite element limit analysis technique with random field method and Monte Carlo simulation technique. To simulate actual field condition, anisotropic random field model of undrained soil shear strength is generated by using the Cholesky-Decomposition method. With the inclusion of a single layer of reinforcement, dimensionless bearing capacity factor, N always increases in both deterministic and probabilistic analysis. As the coefficient of variation of the undrained soil shear strength increases, the mean N value in both unreinforced and reinforced slopes reduces for particular values of correlation length in horizontal and vertical directions. For smaller correlation lengths, the mean N value of unreinforced and reinforced slopes is always lower than the deterministic solutions. However, with the increment in the correlation lengths, this difference reduces and at a higher correlation length, both the deterministic and probabilistic mean values become almost equal. Providing reinforcement under footing subjected to eccentric load is found to be an efficient solution. However, both the deterministic and probabilistic bearing capacity for unreinforced and reinforced slopes reduces with the consideration of loading eccentricity.

• Nuclear Engineering and Technology
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• v.47 no.3
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• pp.306-314
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• 2015

This paper examines the difference in the value of the nuclear fuel cycle cost calculated by the deterministic and probabilistic methods on the basis of an equilibrium model. Calculating using the deterministic method, the direct disposal cost and Pyro-SFR (sodium-cooled fast reactor) nuclear fuel cycle cost, including the reactor cost, were found to be 66.41 mills/kWh and 77.82 mills/kWh, respectively (1 mill = one thousand of a dollar, i.e., $10^{-3}$ $). This is because the cost of SFR is considerably expensive. Calculating again using the probabilistic method, however, the direct disposal cost and Pyro-SFR nuclear fuel cycle cost, excluding the reactor cost, were found be 7.47 mills/kWh and 6.40 mills/kWh, respectively, on the basis of the most likely value. This is because the nuclear fuel cycle cost is significantly affected by the standard deviation and the mean of the unit cost that includes uncertainty. Thus, it is judged that not only the deterministic method, but also the probabilistic method, would also be necessary to evaluate the nuclear fuel cycle cost. By analyzing the sensitivity of the unit cost in each phase of the nuclear fuel cycle, it was found that the uranium unit price is the most influential factor in determining nuclear fuel cycle costs.

• Korean Management Science Review
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• v.27 no.1
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• pp.33-43
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• 2010

This paper presents a method for the estimation and analysis of the economic value of weather forecasts for CRM decision-making problems in the leisure industry. Value is calculated in terms of the customer's satisfaction returned from the user's decision under the specific payoff structure, which is itself represented by a customer's satisfaction ratio model. The decision is assessed by a modified cost-loss model to consider the customer's satisfaction instead of the loss or cost. Site-specific probability and deterministic forecasts, each of which is provided in Korea and China, are applied to generate and analyze the optimal decisions. The application results demonstrate that probability forecasts have greater value than deterministic forecasts, provided that the users can locate the optimal decision threshold. This paper also presents the optimal decision strategy for specific customers with a variety of satisfaction patterns.

• Proceedings of the Korean Geotechical Society Conference
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• 2005.03a
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• pp.129-136
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• 2005

The deterministic analysis method has generally used to evaluate the slope stability and it evaluates the slope stability with decision value that is a representative value of design variables. However, one of disadvantages in the deterministic approach is there is not able to consider the uncertainty of soil strength properties, even though it is the biggest influential parameter of the slope stability. On the other hand, the limit state design(LSD) can take a consideration of uncertainties and computes both the reliability index and the probability of failure. LSD method is capable of overcoming the disadvantages of deterministic method and evaluating the slope stability more reliably. In this study, both the mean value and standard deviation of the internal land's representative soil strength properties applied to process the LSD method. The major purpose of this study is to gauge the general applicability of the limit state design in soil slope and to weigh the comparative validity of the proposed partial safety factor. In order to reach the aim of this study, the partial safety factor and resistance factor which totally satisfied the slope's overall safety factor were calculated by the load and resistance safety factor design (LRFD).

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2003.04a
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• pp.21-26
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• 2003

The well-conditioned observer in a stochastic system is designed so that the observer is less sensitive to the ill-conditioning factors in transient and steady-state observer performance. These factors include not only deterministic issues such as unknown initial estimation error, round-off error, modeling error and sensing bias, but also stochastic issues such as disturbance and sensor noise. In deterministic perspectives, a small value in the L$_2$ norm condition number of the observer eigenvector matrix guarantees robust estimation performance to the deterministic issues and its upper bound can be minimized by reducing the observer gain and increasing the decay rate. Both deterministic and stochastic issues are considered as a weighted sum with a LMI (Linear Matrix Inequality) formulation. The gain in the well-conditioned observer is optimally chosen by the optimization technique. Simulation examples are given to evaluate the estimation performance of the proposed observer.

• Journal of Mechanical Science and Technology
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• v.18 no.10
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• pp.1722-1729
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• 2004

This paper presents a design methodology for determining configurations of slider air bearings considering the randomness of the air-bearing surface (ABS) geometry by using the iSIGHT. A reliability-based design optimization (RBDO) problem is formulated to minimize the variations in the mean values of the flying heights from a target value while satisfying the desired probabilistic constraints keeping the pitch and roll angles within a suitable range. The reliability analysis is employed to estimate how the fabrication tolerances of individual slider parameters affect the final flying attitude tolerances. The proposed approach first solves the deterministic optimization problem. Then, beginning with this solution, the RBDO is continued with the reliability constraints affected by the random variables. Reliability constraints overriding the constraints of the deterministic optimization attempt to drive the design to a reliability solution with minimum increase in the objective. The simulation results of the RBDO are listed in comparison with the values of the initial design and the results of the deterministic optimization, respectively. To show the effectiveness of the proposed approach, the reliability analyses are simply carried out by using the mean value first-order second-moment (MVFO) method. The Monte Carlo simulation of the RBDO's results is also performed to estimate the efficiency of the proposed approach. Those results are demonstrated to satisfy all the desired probabilistic constraints, where the target reliability level for constraints is defined as 0.8.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.11a
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• pp.419-426
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• 2001

Industrial products determined by fixed size posses definite limits variety by manufacture tolerance in existence. The optimum value solved by deterministic approaches do not account of tolerance bands of design variables and material properties. If we examine optimum value considering tolerance bands of design variables and material properties, it might be useless, owing to exist infeasible region. We have two ways to prevent being useless value. The one is to minimize tolerance band, the other is to consider tolerance band in optimum design. The former needed more accuracy during manufacturing process require higher production cost, the letter is more appropriate to consider tolerance band. In this research, we consider the tolerance bands of all variables, which might have the tolerance bands used in the problem, based on optimum value of deterministic approaches. Orthogonal arrays are used to minimize the number of trial. Tolerance bands are supposed discretionary according to design variable. Appropriateness suggested by this research is examined through two examples. Mathematical problem is investigated only in terms of tolerance bands of design variables, and cantilever beam problem is explained through tolerance bands of design variable, material properties and loading conditions. It is proved that values from the presented method are satisfactory for tolerance bands of variables.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.4
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• pp.571-579
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• 1990

A dynamic relocation algorithm for non-deterministic process graph in distributed computer systems is proposed. A method is represented for determining the optimal policy for processing a process tree. A general database query request is modelled by a process tree which represent a set of subprocesses together with their precedence relationship. The process allocation model is based on operating cost which is a function fo selection of site for processing operation, data reduction function and file size. By using expected values of parameters for non-deterministic process tree, the process graph and optimal policy that yield minimum operating cost are determined. As process is relocated according to threshold value and new information of parameters after the execution of low level process for non-deterministic process graph, the assigned state that approximate to optiaml solution is obtained. The proposed algorihtm is heuristic By performing algorithm for sample problems, it is shown that the proposed algorithm is good in obtaining optimal solution.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.5
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• pp.503-510
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• 2004

In this paper, the well-conditioned observer for a stochastic system is designed so that the observer is less sensitive to the ill-conditioning factors in transient and steady-state observer performance. These factors include not only deterministic uncertainties such as unknown initial estimation error, round-off error, modeling error and sensing bias, but also stochastic uncertainties such as disturbance and sensor noise. In deterministic perspectives, a small value in the L$_{2}$ norm condition number of the observer eigenvector matrix guarantees robust estimation performance to the deterministic uncertainties. In stochastic viewpoints, the estimation variance represents the robustness to the stochastic uncertainties and its upper bound can be minimized by reducing the observer gain and increasing the decay rate. Both deterministic and stochastic issues are considered as a weighted sum with a LMI (Linear Matrix Inequality) formulation. The gain in the well-conditioned observer is optimally chosen by the optimization technique. Simulation examples are given to evaluate the estimation performance of the proposed observer.