• 유체기계공업학회:학술대회논문집
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• 유체기계공업학회 2003년도 유체기계 연구개발 발표회 논문집
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• pp.397-403
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• 2003

In an attempt to solve multiobjective optimization problems, weighted sum method is most widely used for the advantage that a designer can consider the relative significance of each object functions by weight values but it can be highly sensitive to weight vector and occasionally yield a deviated optimum from the relative weighting values designer designated because the multiobjective function has the form of simple sum of the product of the weighting values and the object functions in traditional approach. To search the design solution well agree to the designer's weighting values, we proposed new multiobjective function which is the functional of each normalized objective functions and considered to find the design solution comparing the distance between the characteristic line and the ideal optimum. In this study, proposed multiobjective function was applied to design high efficiency and low noise axial flow fan and the result shows this approach will be effective for the case that the qualify of the design can be highly affected by the designer's subjectiveness represented as weighting values in multiobjective design optimization process.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2001년도 추계학술대회(한국공작기계학회)
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• pp.231-236
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• 2001

The goal of multiphase optimization of machine structure is to obtain 1) light weight, 2) statically and dynamically rigid structure. The entire optimization process is carried out in two phases. In the first phase, multiple optimization problem with two objective functions is treated using pareto genetic algorithm. Two objective functions are weight of the structure, and static compliance. In the second phase, maximum receptance is minimized using genetic algorithm. The method is applied to design of quill type machine structure with back column.

• 전자공학회논문지A
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• 제28A권10호
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• pp.847-854
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• 1991

This paper presents a new output phase assignment algorithm which determines the phases of all the nodes in a given boolean network. An estimation function is defined, which is represented by the relation between the literals in the given function expression. A weight function, WT (fi, fj) is defined, which is represented by approximate amount of common subexpression between function fi and fj. Common Subexpression Graph(CSG) is generated for phase selection by the weight function between all given functions. We propose a heuristic algorithm finding subgraph of which sum of weights has maximum by assigning phases into the given functions. The experiments with MCNC benchmarks show the efficiency of the proposed method.

• Steel and Composite Structures
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• 제7권6호
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• pp.421-440
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• 2007

An optimal design method in cooperated with nonlinear inelastic analysis is presented. The proposed nonlinear inelastic method overcomes the difficulties due to incompatibility between the elastic global analysis and the limit state member design in the conventional LRFD method. The genetic algorithm used is a procedure based on Darwinian notions of survival of the fittest, where selection, crossover, and mutation operators are used to look for high performance ones among sections in the database. They are satisfied with the constraint functions and give the lightest weight to the structure. The objective function taken is the total weight of the steel structure and the constraint functions are load-carrying capacity, serviceability, and ductility requirement. Case studies of a planar portal frame, a space two-story frame, and a three-dimensional steel arch bridge are presented.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2002년도 추계학술대회 논문집
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• pp.42-45
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• 2002

In this paper, multiphase optimization of machine Tool structure is presented. The final goal is to obtain 1) light weight, 2) statically and dynamically rigid. and 3) thermally stable structure. The entire optimization process is carried out in three phases. In the first phase, multiple static optimization problem with two objective functions is treated using Pareto genetic algorithm. where two objective functions are weight of the structure and static compliance. In the second phase, maximum receptance is minimized using simple genetic algorithm. And the last phase, thermal deflection to moving heat sources is analyzed using Predictor-Corrector Method. The method is applied to a high speed line center design which takes the shape of back-column structure.

• Communications for Statistical Applications and Methods
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• 제20권6호
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• pp.481-490
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• 2013

Classification is an important research area as data can be easily obtained even if the number of predictors becomes huge. The support vector machine(SVM) is widely used to classify a subject into a predetermined group because it gives sound theoretical background and better performance than other methods in many applications. The SVM can be viewed as a penalized method with the hinge loss function and penalty functions. Instead of $L_2$ penalty function Fan and Li (2001) proposed the smoothly clipped absolute deviation(SCAD) satisfying good statistical properties. Despite the ability of SVMs, they have drawbacks of non-robustness when there are outliers in the data. We develop a robust SVM method using a weight function with the SCAD penalty function based on the local quadratic approximation. We compare the performance of the proposed SVM with the SVM using the $L_1$ and $L_2$ penalty functions.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2003년도 가을 학술발표회 논문집
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• pp.145-152
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• 2003

An optimal design method in cooperated with nonlinear inelastic analysis method is presented. The proposed nonlinear inelastic method overcomes the difficulties due to incompatibility between the elastic global analysis and the limit state member design in the conventional LRFD method. The genetic algorithm uses a procedure based on Darwinian notions of survival of the fittest, where selection, crossover, and mutation operators are used among sections in the database to look for high performance ones. They satisfy the constraint functions and give the lightest weight to the structure. The objective function is set to the total weight of the steel structure and the constraint functions are load-carrying capacities, serviceability, and ductility requirement. Case studies of a three-dimensional frame and a three-dimensional steel arch bridge are presented.

• Structural Engineering and Mechanics
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• 제17권5호
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• pp.707-725
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• 2004

An optimal design method with nonlinear elastic analysis is presented. The proposed nonlinear elastic method overcomes the drawback of the conventional LRFD method that accounts for nonlinear effect by using the moment amplification factors of $B_1$ and $B_2$. The genetic algorithm used is a procedure based on Darwinian notions of survival of the fittest, where selection, crossover, and mutation operators are employed to look for high performance ones among sections in the database. They are satisfied with the constraint functions and give the lightest weight to the structure. The objective function taken is the total weight of the steel structure and the constraint functions are strength, serviceability, and ductility requirement. Case studies of a planar portal frame, a space two-story frame, and a three-dimensional steel arch bridge are presented.

• 설비공학논문집
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• 제20권10호
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• pp.702-709
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• 2008

In this paper, the optimal thermal storage time of an air-conditioning system with slab thermal storage in office building was analyzed on the basis of the gradient method algorithm. The sum of room temperature deviation and heat extraction rate was set to the criterion function. It was calculated that four hours is the optimal thermal storage time under the standard evaluation criterion. Furthermore, some case studies were executed by controlling ratio of weight functions of room temperature deviation and heat extraction rate in criterion function. It is possible to design many kinds of optimal operation of an air-conditioning system with slab thermal storage by controlling ratio of the weight functions in criterion function.

• 대한수학회지
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• 제58권3호
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• pp.609-631
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• 2021

Let C[0, T] denote a generalized analogue of Wiener space, the space of real-valued continuous functions on the interval [0, T]. Define $Z_{\vec{e},n}$ : C[0, T] → ℝⁿ⁺¹ by $$Z_{\vec{e},n}(x)=\(x(0),\;{\int}_0^T\;e_1(t)dx(t),{\cdots},\;{\int}_0^T\;e_n(t)dx(t)\)$$, where e₁,…, e_n are of bounded variations on [0, T]. In this paper we derive a simple evaluation formula for Radon-Nikodym derivatives similar to the conditional expectations of functions on C[0, T] with the conditioning function $Z_{\vec{e},n}$ which has an initial weight and a kind of drift. As applications of the formula, we evaluate the Radon-Nikodym derivatives of various functions on C[0, T] which are of interested in Feynman integration theory and quantum mechanics. This work generalizes and simplifies the existing results, that is, the simple formulas with the conditioning functions related to the partitions of time interval [0, T].