• Journal of Electrical Engineering and Technology
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• v.10 no.3
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• pp.847-858
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• 2015

Control strategy and corresponding parameters have significant impacts on the overall technical and economic characteristics of composite energy storage systems (CESS). A better control strategy and optimized control parameters can be used to improve the economic and technical characteristics of CESS, and determine the maximum power and stored energy capacity of CESS. A novel coordinated control strategy is proposed considering the coordination of various energy storage systems in CESS. To describe the degree of coordination, a new index, i.e. state of charge coordinated response margin of supercapacitor energy storage system, is presented. Based on the proposed control strategy and index, an optimization model was formulated to minimize the total equivalent cost in a given period for two purposes. The one is to obtain optimal control parameters of an existing CESS, and the other is to obtain the integrated optimal results of control parameters, maximum power and stored energy capacity for CESS in a given period. Case studies indicate that the developed index, control strategy and optimization model can be extensively applied to optimize the economic and technical characteristics of CESS. In addition, impacts of control parameters are discussed in detail.

• International Journal of Control, Automation, and Systems
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• v.1 no.3
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• pp.351-357
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• 2003

A method of design optimization for minimization of force ripple and maximization of thrust force in a linear brushless permanent magnet motor without finite element analysis is represented. The design optimization method calculated the driving force in the function of electric and geometric parameters of a linear brushless PM motor using the sequential quadratic programming method. Using electric and geometric parameters obtained by this method, the normalized force ripple is reduced 7.7% (9.7% to 2.0%) and the thrust force is increased 12.88N (111.55N to 124.43N) compared to those not using design optimization.

• International Journal of Control, Automation, and Systems
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• v.4 no.6
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• pp.775-781
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• 2006

An intelligent optimization method for designing Fractional Order PID(FOPID) controllers based on Particle Swarm Optimization(PSO) is presented in this paper. Fractional calculus can provide novel and higher performance extension for FOPID controllers. However, the difficulties of designing FOPID controllers increase, because FOPID controllers append derivative order and integral order in comparison with traditional PID controllers. To design the parameters of FOPID controllers, the enhanced PSO algorithms is adopted, which guarantee the particle position inside the defined search spaces with momentum factor. The optimization performance target is the weighted combination of ITAE and control input. The numerical realization of FOPID controllers uses the methods of Tustin operator and continued fraction expansion. Experimental results show the proposed design method can design effectively the parameters of FOPID controllers.

• Journal of international Conference on Electrical Machines and Systems
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• v.2 no.1
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• pp.16-22
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• 2013

This paper presents the analysis and optimization of air-core permanent magnet linear synchronous motor with overlapping concentrated windings to achieve high thrust density, high thrust per copper losses and low thrust ripple. For the motor design, we adopt equivalent magnetizing current (EMC) method to analyze the magnetic field and give analytical formulae for calculation of motor parameters such as no-load back EMF, dynamic force, thrust density and thrust per copper losses. Further, we proposed a multi-objective optimization by genetic algorithm to search for the optimum parameters. The design optimization is verified by 2-D Finite Element analysis (FEA).

• Korean Journal of Computational Design and Engineering
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• v.15 no.5
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• pp.325-332
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• 2010

A lens system for mobile phone cameras is comprised of various lenses and designed so as to satisfy design requirements for responses such as a modular transfer function (MTF). However, it is difficult to manufacture and assemble camera modules to maintain the same performance compared with the designed camera modules, because of uncertainty. We should always design a lens system by considering uncertainty that can be caused by errors in the manufacturing and assembly process of mobile phone cameras. The robust optimization offers tools of making robust decisions with the consideration of design parameters, uncontrollable parameters, and the variance of the system. Using an efficient reliability analysis method and an optimization algorithm, we obtained robust optimization results that maximize the mean of MTF and minimize the standard deviation and proposed a new robust design process for a lens system.

• Proceedings of the KSME Conference
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• 2003.11a
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• pp.1436-1441
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• 2003

Recently, simulated annealing algorithms have widely been applied to many structural optimization problems. In this paper, simulated annealing, boltzmann annealing, fast annealing and adaptive simulated annealing are applied to optimization of truss structures for improvement quality of objective function and number of function evaluation. These algorithms are classified by cooling schedule. The authors have changed parameters of ASA's cooling schedule and the influence of cooling schedule parameters on structural optimization obtained is discussed. In addition, cooling schedule of BA and ASA mixed is applied to 10 bar-truss structure.

• Computers and Concrete
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• v.11 no.3
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• pp.253-270
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• 2013

The aim of the present paper is to show the application of optimization strategies for the cost of beams in reinforced concrete buildings and to propose pre-sizing parameters. In order for these goals to be met, an optimization software program was developed. The program combines the analysis of structures by the grid model, reinforced concrete sizing, and the simulated annealing optimization heuristic. Sizing is compliant with the NBR 6118 (2007) Brazilian standard, according to which flexural, shearing, torsion, and web reinforcements and serviceability limit states (deflection and crack width limitation) are checked. Besides the dimensions of the situations mentioned above, the influence the cost of each material (steel, concrete and formwork) has on the overall cost of structures was also determined.

• Journal of IKEEE
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• v.24 no.4
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• pp.969-974
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• 2020

Research into hyper parameter optimization (HPO) has recently revived with interest in models containing many hyper parameters, such as deep neural networks. In this paper, we introduce the most widely used HPO methods, such as grid search, random search, and Bayesian optimization, and investigate their characteristics through experiments. The MNIST data set is used to compare results in experiments to find the best method that can be used to achieve higher accuracy in a relatively short time simulation. The learning rate and weight decay have been chosen for this experiment because these are the commonly used parameters in this kind of experiment.

• Steel and Composite Structures
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• v.44 no.2
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• pp.211-224
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• 2022

Multi-objective optimization was conducted to obtain the optimal configuration of a composite sandwich structure with honeycomb-foam hybrid core subjected to underwater shock waves, which can fulfill the demand for light weight and energy efficient design of structures against underwater blast. Effects of structural parameters on the dynamic response of the sandwich structures subjected to underwater shock waves were analyzed numerically, from which the correlations of different parameters to the dynamic response were determined. Multi-objective optimization of the structure subjected to underwater shock waves of which the initial pressure is 30 MPa was conducted based on surrogate modelling method and genetic algorithm. Moreover, optimization results of the sandwich structure subjected to underwater shock waves with different initial pressures were compared. The research can guide the optimal design of composite sandwich structures subjected to underwater shock waves.

• Kyungpook Mathematical Journal
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• v.64 no.1
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• pp.95-111
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• 2024

The filled function method is useful in solving unconstrained global optimization problems. However, depending on the type of function, and parameters used, there are limitations that cause difficultiies in implemenations. Exponential and logarithmic functions lead to the overflow effect, requiring iterative adjustment of the parameters. This paper proposes a polynomial-filled function that has a general form, is non-exponential, nonlogarithmic, non-parameteric, and continuously differentiable. With this newly proposed filled function, the aforementioned shortcomings of the filled function method can be overcome. To confirm the superiority of the proposed filled function algorithm, we apply it to a set of unconstrained global optimization problems. The data derived by numerical implementation shows that the proposed filled function can be used as an alternative algorithm when solving unconstrained global optimization problems.