• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.428-432
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• 2003

Quantitative Feedback Theory (QFT) is one of most effective methods of robust controller design and can be considered as a suitable method for systems with parametric uncertainties. Particularly it allows us to obtain controllers less conservative than other methods like $H_{\infty}$ and ${\mu}$-synthesis. In QFT method, we transform all the uncertainties and desired specifications to some boundaries in Nichols chart and then we have to find the nominal loop transfer function such that satisfies the boundaries and has the minimum high frequency gain. The major drawback of the QFT method is that there is no effective and useful method for finding this nominal loop transfer function. The usual approach to this problem involves loop-shaping in the Nichols chart by manipulating the poles and zeros of the nominal loop transfer function. This process now aided by recently developed computer aided design tools proceeds by trial and error and its success often depends heavily on the experience of the loop-shaper. Thus for the novice and First time QFT user, there is a genuine need for an automatic loop-shaping tool to generate a first-cut solution. In this paper, we approach the automatic QFT loop-shaping problem by using an algorithm involving Linear Programming (LP) techniques and Genetic Algorithm (GA).

• Computers and Concrete
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• v.14 no.3
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• pp.327-345
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• 2014

This paper presents the application of multi-gene genetic programming (MGP) technique for modeling the bond strength of ribbed steel bars in concrete. In this regard, the experimental data of 264 splice beam tests from different technical papers were used for training, validating and testing the model. Seven basic parameters affecting on the bond strength of steel bars were selected as input parameters. These parameters are diameter, relative rib area and yield strength of steel bar, minimum concrete cover to bar diameter ratio, splice length to bar diameter ratio, concrete compressive strength and transverse reinforcement index. The results show that the proposed MGP model can be alternative approach for predicting the bond strength of ribbed steel bars in concrete. Moreover, the performance of the developed model was compared with the building codes' empirical equations for a complete comparison. The study concludes that the proposed MGP model predicts the bond strength of ribbed steel bars better than the existing building codes' equations. Using the proposed MGP model and building codes' equations, a parametric study was also conducted to investigate the trend of the input variables on the bond strength of ribbed steel bars in concrete.

• Computers and Concrete
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• v.21 no.5
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• pp.513-523
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• 2018

Time dependent strain due to creep is a significant factor in structural design. Multi-gene genetic programming (MGGP) and artificial neural network (ANN) are used to develop two models for prediction of creep compliance in concrete. The first model was developed by MGGP technique and the second model by hybridized MGGP-ANN. In the MGGP-ANN, the ANN is working in parallel with MGGP to predict errors in MGGP model. A total of 187 experimental data sets that contain 4242 data points are filtered from the NU-ITI database. These data are used in developing the MGGP and MGGP-ANN models. These models contain six input variables which are: average compressive strength at 28 days, relative humidity, volume to surface ratio, cement type, age at start of loading and age at the creep measurement. Practical equation based on MGGP was developed. A parametric study carried out with a group of hypothetical data generated among the range of data used to check the generalization ability of MGGP and MGGP-ANN models. To confirm validity of MGGP and MGGP-ANN models; two creep prediction code models (ACI209 and CEB), two empirical models (B3 and GL 2000) are used to compare their results with NU-ITI database.

• Management Science and Financial Engineering
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• v.7 no.2
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• pp.59-71
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• 2001

In the present paper, we present method to solve a Fractional Bulk Transportation Problem(FBTP) in which the numerator is quadratic in nature and the denominator is linear. A related (FBTP) is formed whose feasible solutions are ranked to reach an optimal solution of the given problem. The method to find these feasible solutions makes use of parametric programming wherein a series of Ordinary Bulk Transportation Problems are solved by the usual methods.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.13 no.21
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• pp.51-60
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• 1990

In this paper we deal with the miniaml cost network flow problem with uncertain arc capacity constraints. When the arc capacities are fuzzy with linear L-R type membership function, using parametric programming procedure, we reduced it to the deterministic minimal cost network flow problem which can be solved by various typical network flow algorithms. A modified Algorithm using the Out-of-kilter algorithm is developed.

• Journal of the Korean Institute of Landscape Architecture
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• v.49 no.2
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• pp.1-16
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• 2021

The act of design in landscape architecture consists of a concept within a designer's mind, technical representations, and finally, a process of construction. In the 4th Industrial Revolution, the design process is facing many changes due to the rapid development of computer technology and the IT ecosystem. Computer technology was initially developed for simple functions, such as mathematical calculation and graphic representation. However, after the spread of Personal Computers, starting with IBM and Macintosh, programming languages and hardware rapidly developed, algorithms and applications became specialized, and the purpose of using computers became very diverse. This study diagnoses issues concerning the functions and roles that new design methods, such as computational design, parametric design, and algorithmic design, can play in landscape architecture based on changes in the digital society. The study focused on the design methodology using parametric technology, which has recently received the most attention. First, the basis for discussion was developed by examining the main concepts and characteristics of parametric design in modern landscape architecture. Prior research on the use of parametric design in landscape architecture was analyzed, as were the case studies conducted by landscape design firms. As a result, it was confirmed that parametric design has not been sufficiently discussed in terms of the number and diversity of studies compared to other techniques investigated by landscape design firms. Finally, based on the discussion, the study examined specific cases and future possibilities of the parametric design in landscape architecture.

• International Journal of Naval Architecture and Ocean Engineering
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• v.7 no.1
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• pp.100-114
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• 2015

This paper deploys optimization techniques to obtain the optimum hull form of KSUEZMAX at the conditions of full-load draft and design speed. The processes have been carried out using a RaPID-HOP program. The bow and the stern hull-forms are optimized separately without altering neither, and the resulting versions of the two are then combined. Objective functions are the minimum values of wave-making and viscous pressure resistance coefficients for the bow and stern. Parametric modification functions for the bow hull-form variation are SAC shape, section shape (U-V type, DLWL type), bulb shape (bulb height and size); and those for the stern are SAC and section shape (U-V type, DLWL type). WAVIS version 1.3 code is used for the potential and the viscous-flow solver. Prior to the optimization, a parametric study has been conducted to observe the effects of design parameters on the objective functions. SQP has been applied for the optimization algorithm. The model tests have been conducted at a towing tank to evaluate the resistance performance of the optimized hull-form. It has been noted that the optimized hull-form brings 2.4% and 6.8% reduction in total and residual resistance coefficients compared to those of the original hull-form. The propulsive efficiency increases by 2.0% and the delivered power is reduced 3.7%, whereas the propeller rotating speed increases slightly by 0.41 rpm.

• Structural Engineering and Mechanics
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• v.36 no.6
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• pp.759-783
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• 2010

In this paper, compressive strength of carbon fiber reinforced polymer (CFRP) confined concrete cylinders is formulated using a hybrid method coupling genetic programming (GP) and simulated annealing (SA), called GP/SA, and a robust variant of GP, namely multi expression programming (MEP). Straightforward GP/SA and MEP-based prediction equations are derived for the compressive strength of CFRP-wrapped concrete cylinders. The models are constructed using two sets of predictor variables. The first set comprises diameter of concrete cylinder, unconfined concrete strength, tensile strength of CFRP laminate, and total thickness of CFRP layer. The most widely used parameters of unconfined concrete strength and ultimate confinement pressure are included in the second set. The models are developed based on the experimental results obtained from the literature. To verify the applicability of the proposed models, they are employed to estimate the compressive strength of parts of test results that were not included in the modeling process. A sensitivity analysis is carried out to determine the contributions of the parameters affecting the compressive strength. For more verification, a parametric study is carried out and the trends of the results are confirmed via some previous studies. The GP/SA and MEP models are able to predict the ultimate compressive strength with an acceptable level of accuracy. The proposed models perform superior than several CFRP confinement models found in the literature. The derived models are particularly valuable for pre-design purposes.

• Journal of Korean Society of Transportation
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• v.32 no.4
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• pp.369-379
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• 2014

The Statistical regression model has been used to construct crash prediction models, despite its limitations in assuming data distribution and functional form. In response to the limitations associated with the statistical regression models, a few studies based on non-parametric methods such as neural networks have been proposed to develop crash prediction models. However, these models have a major limitation in that they work as black boxes, and therefore cannot be directly used to identify the relationships between crash frequency and crash factors. A genetic programming model can find a solution to a problem without any specified assumptions and remove the black box effect. Hence, this paper investigates the application of the genetic programming technique to develope the crash prediction model. The data collected from the Gyeongbu expressway during the past three years (2010-2012), were separated into straight and curve sections. The random forest technique was applied to select the important variables that affect crash occurrence. The genetic programming model was developed based on the variables that were selected by the random forest. To test the goodness of fit of the genetic programming model, the RMSE of each model was compared to that of the negative binomial regression model. The test results indicate that the goodness of fit of the genetic programming models is superior to that of the negative binomial models.

• Korean Journal of Computational Design and Engineering
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• v.9 no.2
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• pp.93-101
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• 2004

In mechanical design, optimization procedures have mostly been implemented solely by CAE codes combined by optimization routine, in which the model is built, analyzed and optimized. In the complex geometries, however, CAD is indispensable tool for the efficient and accurate modeling. This paper presents a method to carry out optimization, in which CAD and CAE are used for modeling and analysis respectively and integrated in an optimization routine. Application Programming Interface (API) function is exploited to automate CAD modeling, which enables direct access to CAD. The advantage of this method is that the user can create very complex object in Parametric and automated way, which is impossible in CAE codes. Unigraphics and ANSYS are adopted as CAD and CAE tools. In ANSYS, automated analysis is done using codes made by a script language, APDL(ANSYS Parametric Design Language). Optimization is conducted by VisualDOC and IDESIGN respectively. As an illustrative example, a mold design problem is studied, which is to minimize temperature deviation over a diagonal line of the surface of the mold in contact with hot glass.