• International Journal of Aeronautical and Space Sciences
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• v.14 no.4
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• pp.334-340
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• 2013

This paper deals with the optimization of blade stiffened composite panels. The main objective of the research is to make response surfaces for the constraints. The response surface for warping thermal deformation was previously made for a fixed dimension composite structure. In this study, the dimensions of the blade stiffener were treated as design variables. This meant that a new response surface technique was required for the constraints. For the response surfaces, the lamination parameters, linear thermal expansions and dimensions of the structures were used as variables. A genetic algorithm was adopted as an optimizer, and an optimal result, which satisfied two constraints, was obtained. As a result, a new response surface was obtained, for predicting warping thermal deformation.

• Proceedings of the KSR Conference
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• 2009.05a
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• pp.1557-1565
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• 2009

According to the GM/RT2141, to assess the safety of vehicle, the validated the vehicle dynamic model should be applied. The validation of the vehicle model is against the static test, some kind of vehicle type test results have been used to determine the suspension characteristics and the vehicle dynamic characteristics. To validate the vehicle model and the test results, first the test results has been analysed as to specified the suspension characteristics and than the parameters to related with the test result has to be adjusted to show the same results of the test. In this process the parameters of vehicle model have been determined to show the coherence of the two results of the simulation and the test by trial & error. In this report, the optimization tool has been introduced in this model validation process and shows the efficient and well validated model.

• Journal of the Semiconductor & Display Technology
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• v.16 no.1
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• pp.59-64
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• 2017

The general manufacturing problem can be described as the achievement of a predefined product quality with given equipment, cost and time constraints. Unfortunately, for some quality characteristics of a product such as surface roughness it is hard to ensure that these requirements will be met. Stainless steels STS 304 is frequently used as shaft materials in small fiber reinforced polymer(FRP) fishing boats. In this work, the dry turning parameters of STS 304 are optimized by using Taguchi method. The experiments were conducted at three different cutting speeds with three different feed and three different depth of cut. The cutting parameters are optimized using signal to noise ratio and the analysis of variance. The effects of cutting speed and feed on surface roughness was analyzed. The results revealed that the spindle speed is the more significant parameter influencing the surface roughness.

• Journal of Welding and Joining
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• v.18 no.6
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• pp.96-101
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• 2000

Sintered alumina ceramic substrate has been used for the insulating substrate for thick Hybrid IC owing to its cheapness and good insulating properties. Some of thick HIC's are important to eliminate the heat emitted from the parts that are mounted on the ceramic substrate. Sintered ceramic substrate can not transfer and emit the heat efficiently. It's been tried to do plasma spray coating of alumina ceramic on the metal substrates that have a good heat emission property. The most important properties to commercialize this ceramic coated metal substrate are surface roughness and deposition efficiency. In this study, plasma spray coating parameters are optimized to minimize the surface roughness and to maximize the deposition efficiency using Taguchi experimental method. By this optimization, the deposition efficiency was greatly improved from 35% at the frist time to 75% finally.

• International Journal of Control, Automation, and Systems
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• v.2 no.3
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• pp.298-309
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• 2004

In this paper, a new evolutionary scheme to design a TSK fuzzy model from relevant data is proposed. The identification of the antecedent rule parameters is performed via the evolutionary algorithm with the unique fitness function and the various evolutionary operators, while the identification of the consequent parameters is done using the least square method. The occurrence of the multiple overlapping membership functions, which is a typical feature of unconstrained optimization, is resolved with the help of the proposed fitness function. The proposed algorithm can generate a fuzzy model with transparent membership functions. Through simulations on various problems, the proposed algorithm found a TSK fuzzy model with better accuracy than those found in previous works with transparent partition of input space.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.623-627
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• 1995

This paper describes analysis and optimization of Weil-Dobke synthetic testing circuit parameters, which is efficient and economical test method in high capacity AC circuit breaker. In this paper, analysis of synthetic short-circuit test circuit parameter proposed nondimensional factor that is reciprocal comparison value of circuit parameter and is not related to rated of circuit breaker, in particular, this study induce minimization of required energy of critical TRV generation specified in IEC 56 standards and present optimal design of synthetic short circuit testing facilities.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.3
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• pp.253-258
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• 2005

In this study, we introduce a new category of fuzzy inference systems based on information granulation to carry out the model identification of complex and nonlinear systems. Informal speaking, information granules are viewed as linked collections of objects (data, in particular) drawn together by the criteria of proximity, similarity, or functionality. To identify the structure of fuzzy rules we use genetic algorithms (GAs). Granulation of information with the aid of Hard C-Means (HCM) clustering algorithm help determine the initial parameters of fuzzy model such as the initial apexes of the membership functions and the initial values of polynomial functions being used in the premise and consequence part of the fuzzy rules. And the initial parameters are tuned effectively with the aid of the genetic algorithms and the least square method (LSM). The proposed model is contrasted with the performance of the conventional fuzzy models in the literature.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.12
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• pp.985-992
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• 2001

This paper proposes a self-organizing fuzzy modeling(SOFUM)which an create a new hyperplane shaped cluster and adjust parameters of the fuzzy model in repetition. The suggested algorithm SOFUM is composed of four steps: coarse tuning. fine tuning cluster creation and optimization of learning rates. In the coarse tuning fuzzy C-regression model(FCRM) clustering and weighted recursive least squared (WRLS) algorithm are used and in the fine tuning gradient descent algorithm is used to adjust parameters of the fuzzy model precisely. In the cluster creation, a new hyperplane shaped cluster is created by applying multiple regression to input/output data with relatively large fuzzy entropy based on parameter tunings of fuzzy model. And learning rates are optimized by utilizing meiosis-genetic algorithm in the optimization of learning rates To check the effectiveness of the suggested algorithm two examples are examined and the performance of the identified fuzzy model is demonstrated via computer simulation.

• Journal of the Semiconductor & Display Technology
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• v.14 no.4
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• pp.78-83
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• 2015

The method of electrical discharge machining (EDM), one of the processing methods based on non-traditional manufacturing procedures, is gaining increased popularity, since it does not require cutting tools and allows machining involving hard, brittle, thin and complex geometry. Modern ED machinery is capable of machining geometrically complex or hard material components, that are precise and difficult-to-machine such as heat treated tool steels, composites, super alloys, ceramics, etc. This paper reports the results of an experimental investigation by Taguchi method carried out to study the effects of machining parameters on material surface roughness in electric discharge machining of SM45C. The work material was ED machined with graphite and copper electrodes by varying the pulsed current, voltage and pulse time. Investigations indicate that the surface roughness is strongly depend on pulsed current.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.8A
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• pp.650-656
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• 2003

In 1995, a group of representatives from the integrated circuits and computer-aided design industries presented a industry standard bipolar model called the VBIC model. The VBIC model includes the improved Early effect, quasi-saturation, substrate parasitic, avalanche multiplication, and self-heating which are not available in the conventional SGP model. This paper applies VBIC model for SiGe HBT device and develops an accurate and efficient methodology to extract all the DC and AC parameters of the VBIC model for SiGe HBT device at room temperature. Simulated results by the extracted VBIC model parameter are compared with the measurement data and show very good agreement in both DC and s-parameters prediction.