• Communications for Statistical Applications and Methods
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• v.14 no.3
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• pp.507-516
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• 2007

Multinomial logistic regression is probably the most popular representative of probabilistic discriminative classifiers for multiclass classification problems. In this paper, a kernel variant of multinomial logistic regression is proposed by combining a Newton's method with a bound optimization approach. This formulation allows us to apply highly efficient approximation methods that effectively overcomes conceptual and numerical problems of standard multiclass kernel classifiers. We also provide the approximate cross validation (ACV) method for choosing the hyperparameters which affect the performance of the proposed approach. Experimental results are then presented to indicate the performance of the proposed procedure.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.4
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• pp.1276-1295
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• 2023

Sensor networks are now an essential aspect of wireless communication, especially with the introduction of new gadgets and protocols. Their ability to be deployed anywhere, especially where human presence is undesirable, makes them perfect choices for remote observation and control. Despite their vast range of applications from home to hostile territory monitoring, limited battery power remains a limiting factor in their efficacy. To analyze and transmit data, it requires intelligent use of available battery power. Several studies have established effective routing algorithms based on clustering. However, choosing optimal cluster heads and similarity measures for clustering significantly increases computing time and cost. This work proposes and implements a simple two-phase technique of route creation and maintenance to ensure route reliability by employing nature-inspired ant colony optimization followed by the fuzzy decision engine (FDE). Benchmark methods such as PSO, ACO and GWO are compared with the proposed HRCM's performance. The objective has been focused towards establishing the superiority of proposed work amongst existing optimization methods in a standalone configuration. An average of 15% improvement in energy consumption followed by 12% improvement in latency reduction is observed in proposed hybrid model over standalone optimization methods.

• Journal of Electrical Engineering and Technology
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• v.7 no.4
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• pp.501-512
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• 2012

Social welfare maximization in a double-sided auction market is performed by implementing an aggregation-based particle swarm optimization (CAPSO) algorithm for optimal placement and sizing of one Static Synchronous Series Compensator (SSSC) device. Dallied simulation results (without/with line flow constraints and without/with SSSC) are generated to demonstrate the impact of SSSC on the congestion levels of the modified IEEE 14-bus test system. The proposed CAPSO algorithm employs conventional quadratic smooth and augmented quadratic nonsmooth generator cost curves with sine components to improve the accurate of the model by incorporating the valve loading effects. CAPSO also employs quadratic smooth consumer benefit functions. The proposed approach relies on particle swarm optimization to capture the near-optimal GenCos and DisCos, as well as the location and rating of SSSC while the Newton based load flow solution minimizes the mismatch equations. Simulation results of the proposed CAPSO algorithm are compared to solutions obtained by sequential quadratic programming (SQP) and a recently implemented Fuzzy based genetic algorithm (Fuzzy-GA). The main contributions are inclusion of customer benefit in the congestion management objective function, consideration of nonsmooth generator characteristics and the utilization of a coordinated aggregation-based PSO for locating/sizing of SSSC.

• Journal of Korean Association for Spatial Structures
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• v.21 no.4
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• pp.49-56
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• 2021

This study aims to develop a form-finding algorithm for a single-layered pneumatic membrane. The initial shape of this pneumatic membrane, which is an air-supported type pneumatic membrane, is to find a state in which a given initial tension and internal pneumatic pressure are in equilibrium. The algorithm developed to satisfy these conditions is that a nonlinear optimization problem based on the force method considering the deformed shape is formulated, and, it's able to find the shape by iteratively repeating the process of obtaining a solution of the governing equations. An computational technique based on the Gauss-Newton method was used as a method for obtaining solutions of nonlinear equations. In order to verify the validity of the proposed form-finding algorithm, a single-curvature pneumatic membrane example and a double-curvature air pneumatic membrane example were adopted, respectively. In the results of these examples, it was possible to well observe the step-by-step convergence process of the shape of the pneumatic membrane, and it was also possible to confirm the change in shape according to the air pressure. In addition, the calculation results of the shape and internal force after deformation due to initial tension, air pressure, and self-weight were obtained.

• Water Engineering Research
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• v.2 no.3
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• pp.161-169
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• 2001

Present study deals with the development of a numerical model for the estimation of net annual recharge by coupling the Galerkin's finite element flow simulationl model with the Gauss-Newton-Marquardt optimization technique. The developed coupled numerical model is applied for estimating net annual recharge for Mahi Right Bank Canal (MRBC) project the norms of Groundwater Resources Estimation committee (1984, 1997) and Indian Agricultural research Institute(1983). It is observed that the estimated net recharge by inverse modeling is closer to the net recharge estimated using the water balance approach. Further it is observed that the computed head distribution from the estimated recharge agree closely with the observed head distribution. The study concludes that the developed model for inverse modeling can be successfully applied to large groundwater system involving regional aquifers where reliable recharge estimation always requires considerable time and financial resources.

• Journal of Mechanical Science and Technology
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• v.15 no.11
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• pp.1563-1571
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• 2001

The effect of flow distribution on thermal and flow performance of a parallel flow heat exchanger has been numerically investigated. The flow distribution has been altered by varying the geometrica l parameters that included the locations of the separators, and the inlet/outlet of the heat exchanger. Flow nonuniformities along paths of the heat exchanger, which were believed to be dominantly influential to the thermal performance, have been observed to eventually optimize the design of the heat exchanger. The optimization has been accomplished by minimizing the flow nonuniformity that served as an object function when the Newton's searching method was applied. It was found that the heat transfer of the optimized model increased approximately 7.6%, and the pressure drop decreased 4.7%, compared to those of the base model of the heat exchanger.

• Proceedings of the Korean Information Science Society Conference
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• 2004.04b
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• pp.721-723
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• 2004

A trust-region method is a quite attractive optimization technique. It is, in general, faster than the steepest descent method and is free of a learning rate unlike the gradient-based methods. In addition to its convergence property (between linear and quadratic convergence), ifs stability is always guaranteed, in contrast to the Newton's method. In this paper, we present an efficient implementation of the maximum likelihood independent component analysis (ICA) using the trust-region method, which leads to trust-region-based ICA (TR-ICA) algorithms. The useful behavior of our TR-ICA algorithms is confimed through numerical experimental results.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.6
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• pp.3448-3454
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• 2014

Generally existing structure analysis was applied to elastic analysis basically in practice. Considering the nonlinear material and the nonlinear geometric to be a more precise analysis, for this reason, The necessity for a structual analysis have been constantly required. Therefore, after optimization is performed, designed a simple model which is applied the principle of nonlinear in this study, a structural analysis of existing experienced users, have a aims at presenting theory and a method in order to perform anyone the analysis easily. In this study, the proposed model applied to die ribs, Regarding the shear load, less strain and stress was generated but strength was sufficient. The initial strain and stress was reconfigured to fit the size and shape, A hyperstudy in conjunction with Abaqus with nonlinear structural analysis, revealed an acceptable maximum and minimum range of stress and under the conditions of minimum strain, the plate made with a constant increment. In the experimental models, the plate thickness was given a power of 40 Newton, according to the thickness of the press die through an iterative process. When the stress and strain was applied to the die thickness, 7-8mm thickness could be obtained by optimizing.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.7 no.3
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• pp.141-154
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• 1987

The algorithm proposed utilizes the tow-levels technique. In the first level which consists of teeatment only the applied load and design stress as the random variables whose parent distribution has the normal distribution, the cross-sectional areas of the truss members such that the their probabilities of failure have the preseribed failure probabilites are optimized by transforming the nonlinear problem into SUMT, and solving it utilizing modified Newton-Raphson method. In the second level, the geometric shape of truss structure is optimized by utilizing the unidirectional search technique of Powell method which makes it possible to minimize only the objective function. The algorithm proposed is numerically tested for the several truss structures with various shapes and loading conditions. The numerical analysis shows that the rate of decreasing the weight of truss structures is dependent on the prescribed failure probability of the each member of truss structure and the covariance of the applied load and design stress.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.15 no.4
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• pp.661-674
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• 2002

The objective of this study is to develop efficient numerical method to enable solution of optimal control problems of Navier-Stokes flows and to apply these technique to the problem of viscous drag minimization on a bluff body by controlling boundary velocities on the surface of the body. In addition to the industrial importance of the drag reduction problem, it serves as a model for other more complex flow optimization settings, and allows us to study, modify, and improve the behavior of the optimal control methods proposed here. The control is affected by the suction or injection of fluid on portions of the boundary, and the objective function represents the rate at which energy is dissipated in the fluid. This study shows how reduced Hessian successive quadratic programming method, which avoid converging the flow equations at each iteration, can be tailored to these problems.