• Title/Summary/Keyword: real-valued functions

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Common Fixed Point Theorems of Commuting Mappinggs

  • Park, Wee-Tae
    • The Mathematical Education
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    • v.26 no.1
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    • pp.41-45
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    • 1987
  • In this paper, we give several fixed point theorems in a complete metric space for two multi-valued mappings commuting with two single-valued mappings. In fact, our main theorems show the existence of solutions of functional equations f($\chi$)=g($\chi$)$\in$S$\chi$∩T$\chi$ and $\chi$=f($\chi$)=g($\chi$)$\in$S$\chi$∩T$\chi$ under certain conditions. We also answer an open question proposed by Rhoades-Singh-Kulsherestha. Throughout this paper, let (X, d) be a complete metric space. We shall follow the following notations : CL(X) = {A; A is a nonempty closed subset of X}, CB(X)={A; A is a nonempty closed and founded subset of X}, C(X)={A; A is a nonempty compact subset of X}, For each A, B$\in$CL(X) and $\varepsilon$>0, N($\varepsilon$, A) = {$\chi$$\in$X; d($\chi$, ${\alpha}$) < $\varepsilon$ for some ${\alpha}$$\in$A}, E$\sub$A, B/={$\varepsilon$ > 0; A⊂N($\varepsilon$ B) and B⊂N($\varepsilon$, A)}, and (equation omitted). Then H is called the generalized Hausdorff distance function fot CL(X) induced by a metric d and H defined CB(X) is said to be the Hausdorff metric induced by d. D($\chi$, A) will denote the ordinary distance between $\chi$$\in$X and a nonempty subset A of X. Let R$\^$+/ and II$\^$+/ denote the sets of nonnegative real numbers and positive integers, respectively, and G the family of functions ${\Phi}$ from (R$\^$+/)$\^$s/ into R$\^$+/ satisfying the following conditions: (1) ${\Phi}$ is nondecreasing and upper semicontinuous in each coordinate variable, and (2) for each t>0, $\psi$(t)=max{$\psi$(t, 0, 0, t, t), ${\Phi}$(t, t, t, 2t, 0), ${\Phi}$(0, t, 0, 0, t)} $\psi$: R$\^$+/ \longrightarrow R$\^$+/ is a nondecreasing upper semicontinuous function from the right. Before sating and proving our main theorems, we give the following lemmas:

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SCALE TRANSFORMATIONS FOR PRESENT POSITION-INDEPENDENT CONDITIONAL EXPECTATIONS

  • Cho, Dong Hyun
    • Journal of the Korean Mathematical Society
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    • v.53 no.3
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    • pp.709-723
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    • 2016
  • Let C[0, t] denote a generalized Wiener space, the space of real-valued continuous functions on the interval [0, t] and define a random vector $Z_n:C[0,t]{\rightarrow}{\mathbb{R}}^n$ by $Zn(x)=(\int_{0}^{t_1}h(s)dx(s),{\cdots},\int_{0}^{t_n}h(s)dx(s))$, where 0 < $t_1$ < ${\cdots}$ < $t_n$ < t is a partition of [0, t] and $h{\in}L_2[0,t]$ with $h{\neq}0$ a.e. In this paper we will introduce a simple formula for a generalized conditional Wiener integral on C[0, t] with the conditioning function $Z_n$ and then evaluate the generalized analytic conditional Wiener and Feynman integrals of the cylinder function $F(x)=f(\int_{0}^{t}e(s)dx(s))$ for $x{\in}C[0,t]$, where $f{\in}L_p(\mathbb{R})(1{\leq}p{\leq}{\infty})$ and e is a unit element in $L_2[0,t]$. Finally we express the generalized analytic conditional Feynman integral of F as two kinds of limits of non-conditional generalized Wiener integrals of polygonal functions and of cylinder functions using a change of scale transformation for which a normal density is the kernel. The choice of a complete orthonormal subset of $L_2[0,t]$ used in the transformation is independent of e and the conditioning function $Z_n$ does not contain the present positions of the generalized Wiener paths.

Global Optimization Using Kriging Metamodel and DE algorithm (크리깅 메타모델과 미분진화 알고리듬을 이용한 전역최적설계)

  • Lee, Chang-Jin;Jung, Jae-Jun;Lee, Kwang-Ki;Lee, Tae-Hee
    • Proceedings of the KSME Conference
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    • 2001.06c
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    • pp.537-542
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    • 2001
  • In recent engineering, the designer has become more and more dependent on computer simulation. But defining exact model using computer simulation is too expensive and time consuming in the complicate systems. Thus, designers often use approximation models, which express the relation between design variables and response variables. These models are called metamodel. In this paper, we introduce one of the metamodel, named Kriging. This model employs an interpolation scheme and is developed in the fields of spatial statistics and geostatistics. This class of interpolating model has flexibility to model response data with multiple local extreme. By reason of this multi modality, we can't use any gradient-based optimization algorithm to find global extreme value of this model. Thus we have to introduce global optimization algorithm. To do this, we introduce DE(Differential Evolution). DE algorithm is developed by Ken Price and Rainer Storn, and it has recently proven to be an efficient method for optimizing real-valued multi-modal objective functions. This algorithm is similar to GA(Genetic Algorithm) in populating points, crossing over, and mutating. But it introduces vector concept in populating process. So it is very simple and easy to use. Finally, we show how we determine Kriging metamodel and find global extreme value through two mathematical examples.

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Simulated Annealing Algorithm Using Cauchy-Gaussian Probability Distributions (Cauchy와 Gaussian 확률 분포를 이용한 Simulated Annealing 알고리즘)

  • Lee, Dong-Ju;Lee, Chang-Yong
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.33 no.3
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    • pp.130-136
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    • 2010
  • In this study, we propose a new method for generating candidate solutions based on both the Cauchy and the Gaussian probability distributions in order to use the merit of the solutions generated by these distributions. The Cauchy probability distribution has larger probability in the tail region than the Gaussian distribution. Thus, the Cauchy distribution can yield higher probabilities of generating candidate solutions of large-varied variables, which in turn has an advantage of searching wider area of variable space. On the contrary, the Gaussian distribution can yield higher probabilities of generating candidate solutions of small-varied variables, which in turn has an advantage of searching deeply smaller area of variable space. In order to compare and analyze the performance of the proposed method against the conventional method, we carried out experiments using benchmarking problems of real valued functions. From the result of the experiment, we found that the proposed method based on the Cauchy and the Gaussian distributions outperformed the conventional one for most of benchmarking problems, and verified its superiority by the statistical hypothesis test.

A Study on Multi-objective Optimal Power Flow under Contingency using Differential Evolution

  • Mahdad, Belkacem;Srairi, Kamel
    • Journal of Electrical Engineering and Technology
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    • v.8 no.1
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    • pp.53-63
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    • 2013
  • To guide the decision making of the expert engineer specialized in power system operation and control; the practical OPF solution should take in consideration the critical situation due to severe loading conditions and fault in power system. Differential Evolution (DE) is one of the best Evolutionary Algorithms (EA) to solve real valued optimization problems. This paper presents simple Differential Evolution (DE) Optimization algorithm to solving multi objective optimal power flow (OPF) in the power system with shunt FACTS devices considering voltage deviation, power losses, and power flow branch. The proposed approach is examined and tested on the standard IEEE-30Bus power system test with different objective functions at critical situations. In addition, the non smooth cost function due to the effect of valve point has been considered within the second practical network test (13 generating units). The simulation results are compared with those by the other recent techniques. From the different case studies, it is observed that the results demonstrate the potential of the proposed approach and show clearly its effectiveness to solve practical OPF under contingent operation states.

Oscillation of Second-Order Nonlinear Forced Functional Dynamic Equations with Damping Term on Time Scales

  • Agwa, Hassan Ahmed;Khodier, Ahmed Mahmoud;Ahmed, Heba Mostaafa Atteya
    • Kyungpook Mathematical Journal
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    • v.56 no.3
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    • pp.777-789
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    • 2016
  • In this paper, we establish some new oscillation criteria for the second-order forced nonlinear functional dynamic equations with damping term $$(r(t)x^{\Delta}(t))^{\Delta}+q({\sigma}(t))x^{\Delta}(t)+p(t)f(x({\tau}(t)))=e(t)$$, and $$(r(t)x^{\Delta}(t))^{\Delta}+q(t)x^{\Delta}(t)+p(t)f(x({\sigma}(t)))=e(t)$$, on a time scale ${\mathbb{T}}$, where r(t), p(t) and q(t) are real-valued right-dense continuous (rd-continuous) functions [1] defined on ${\mathbb{T}}$ with p(t) < 0 and ${\tau}:{\mathbb{T}}{\rightarrow}{\mathbb{T}}$ is a strictly increasing differentiable function and ${\lim}_{t{\rightarrow}{\infty}}{\tau}(t)={\infty}$. No restriction is imposed on the forcing term e(t) to satisfy Kartsatos condition. Our results generalize and extend some pervious results [5, 8, 10, 11, 12] and can be applied to some oscillation problems that not discussed before. Finally, we give some examples to illustrate our main results.

Function Optimization and Event Clustering by Adaptive Differential Evolution (적응성 있는 차분 진화에 의한 함수최적화와 이벤트 클러스터링)

  • Hwang, Hee-Soo
    • Journal of the Korean Institute of Intelligent Systems
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    • v.12 no.5
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    • pp.451-461
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    • 2002
  • Differential evolution(DE) has been preyed to be an efficient method for optimizing real-valued multi-modal objective functions. DE's main assets are its conceptual simplicity and ease of use. However, the convergence properties are deeply dependent on the control parameters of DE. This paper proposes an adaptive differential evolution(ADE) method which combines with a variant of DE and an adaptive mechanism of the control parameters. ADE contributes to the robustness and the easy use of the DE without deteriorating the convergence. 12 optimization problems is considered to test ADE. As an application of ADE the paper presents a supervised clustering method for predicting events, what is called, an evolutionary event clustering(EEC). EEC is tested for 4 cases used widely for the validation of data modeling.

LARGE TIME ASYMPTOTICS OF LEVY PROCESSES AND RANDOM WALKS

  • Jain, Naresh C.
    • Journal of the Korean Mathematical Society
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    • v.35 no.3
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    • pp.583-611
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    • 1998
  • We consider a general class of real-valued Levy processes {X(t), $t\geq0$}, and obtain suitable large deviation results for the empiricals L(t, A) defined by $t^{-1}{\int^t}_01_A$(X(s)ds for t > 0 and a Borel subset A of R. These results are used to obtain the asymptotic behavior of P{Z(t) < a}, where Z(t) = $sup_{u\leqt}\midx(u)\mid$ as $t\longrightarrow\infty$, in terms of the rate function in the large deviation principle. A subclass of these processes is the Feller class: there exist nonrandom functions b(t) and a(t) > 0 such that {(X(t) - b(t))/a(t) : t > 0} is stochastically compact, i.e., each sequence has a weakly convergent subsequence with a nondegenerate limit. The stable processes are in this class, but it is much larger. We consider processes in this class for which b(t) may be taken to be zero. For any t > 0, we consider the renormalized process ${X(u\psi(t))/a(\psi(t)),u\geq0}$, where $\psi$(t) = $t(log log t)^{-1}$, and obtain large deviation probability estimates for $L_{t}(A)$ := $(log log t)^{-1}$${\int_{0}}^{loglogt}1_A$$(X(u\psi(t))/a(\psi(t)))dv$. It turns out that the upper and lower bounds are sharp and depend on the entire compact set of limit laws of {X(t)/a(t)}. The results extend to random walks in the Feller class as well. Earlier results of this nature were obtained by Donsker and Varadhan for symmetric stable processes and by Jain for random walks in the domain of attraction of a stable law.

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CHANGE OF SCALE FORMULAS FOR A GENERALIZED CONDITIONAL WIENER INTEGRAL

  • Cho, Dong Hyun;Yoo, Il
    • Bulletin of the Korean Mathematical Society
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    • v.53 no.5
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    • pp.1531-1548
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    • 2016
  • Let C[0, t] denote the space of real-valued continuous functions on [0, t] and define a random vector $Z_n:C[0,t]{\rightarrow}\mathbb{R}^n$ by $Z_n(x)=(\int_{0}^{t_1}h(s)dx(s),{\ldots},\int_{0}^{t_n}h(s)dx(s))$, where 0 < $t_1$ < ${\cdots}$ < $ t_n=t$ is a partition of [0, t] and $h{\in}L_2[0,t]$ with $h{\neq}0$ a.e. Using a simple formula for a conditional expectation on C[0, t] with $Z_n$, we evaluate a generalized analytic conditional Wiener integral of the function $G_r(x)=F(x){\Psi}(\int_{0}^{t}v_1(s)dx(s),{\ldots},\int_{0}^{t}v_r(s)dx(s))$ for F in a Banach algebra and for ${\Psi}=f+{\phi}$ which need not be bounded or continuous, where $f{\in}L_p(\mathbb{R}^r)(1{\leq}p{\leq}{\infty})$, {$v_1,{\ldots},v_r$} is an orthonormal subset of $L_2[0,t]$ and ${\phi}$ is the Fourier transform of a measure of bounded variation over $\mathbb{R}^r$. Finally we establish various change of scale transformations for the generalized analytic conditional Wiener integrals of $G_r$ with the conditioning function $Z_n$.

Customer-Centric CRM Implementation Case Study (고객중심의 CRM 구축비교 사례연구)

  • Lee, Ho-Seoub
    • Management & Information Systems Review
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    • v.23
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    • pp.25-40
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    • 2007
  • In the highly competitive and divers world of financial market, customer is the single most important factor to company's survival. Especially, creating a relationship with valued customers is a key to success. CRM provides the mean to retain high value customers. It takes a prospect of what customers expect. Utilizing those knowledge can help the products and service meet the customers' needs, thereby maximizing customer satisfaction and company's profit. In this report, I am going to suggest a few ways to develop successful CRM in the life insurance industry. First, CRM should innovate the way of communication to keep pace with Web 2.0 era. In other words, the customer's needs should be caught by real-time communication than traditional off-line market research. Thus, the functionality and specification of products can be decided by customer's direct choice so that the customers are able to purchase the understanding and experience of the products. Second, CRM project should consider whether the initial strategy plan can promise the stable growth of customer at the first step. When planning strategy, the project needs to identify what customer wants and how to fulfill the needs with stable growth of the customer. In addition, the CRM should be developed by realizing that customer centric benefits ultimately guarantee the growth of the organization. Third, CRM systems should enhance the organization's ability to take the customer's insight in a 360 degree view and to capture the voice of the customer directly. In order to develop the best matched product package, more precise customer segmentation should be ahead of market segmentation strategy. Forth, the biggest reward from CRM will be a customer royalty program. Many successful banks are already planning and practicing customer royalty strategy. A comprehensive analysis of customers and their behavior allow organization to identify high value potential customers' needs and determine a strategy required to meet those needs. Even life insurance companies such as Prudential Korea are developing products designed for royal customers. Fifth, understanding and managing the experience of customer called Customer Experience Management also can increase customer satisfaction. Measuring only customers' experience and adapting it to marketing strategy make products position in the gap between the customers' expectation and experience not required by market. A key component of CEM is its application across all organizational functions. At last, the direction of change and development of CRM can be defined from the conceptualization of information technology represented by Ubiquitous and Web 2.0. Instead of just managing customer information, companies should take the initiative in personalized system with customer oriented strategy. Furthermore, with the regular communication between CRM stakeholders (Sales-Marketing-IT), customer's demand should be directly reflected to enterprise strategy in real time.

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