• 제목/요약/키워드: Business mathematics

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FOUR LOGARITHMICALLY COMPLETELY MONOTONIC FUNCTIONS INVOLVING GAMMA FUNCTION

  • Qi, Feng;Niu, Da-Wei;Cao, Jian;Chen, Shou-Xin
    • Journal of the Korean Mathematical Society
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    • v.45 no.2
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    • pp.559-573
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    • 2008
  • In this paper, two classes of functions, involving a parameter and the classical Euler gamma function, and two functions, involving the classical Euler gamma function, are verified to be logarithmically completely monotonic in $(-\frac{1}{2},\infty)$ or $(0,\infty)$; some inequalities involving the classical Euler gamma function are deduced and compared with those originating from certain problems of traffic flow, due to J. Wendel and A. Laforgia, and relating to the well known Stirling's formula.

SOLUTIONS OF STURM-LIOUVILLE BOUNDARY VALUE PROBLEMS FOR HIGHER-ORDER DIFFERENTIAL EQUATIONS

  • Liu, Yuji
    • Journal of applied mathematics & informatics
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    • v.24 no.1_2
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    • pp.231-243
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    • 2007
  • The existence of solutions of a class of two-point boundary value problems for higher order differential equations is studied. Sufficient conditions for the existence of at least one solution are established. It is of interest that the nonlinearity f in the equation depends on all lower derivatives, and the growth conditions imposed on f are allowed to be super-linear (the degrees of phases variables are allowed to be greater than 1 if it is a polynomial). The results are different from known ones since we don't apply the Green's functions of the corresponding problem and the method to obtain a priori bound of solutions are different enough from known ones. Examples that can not be solved by known results are given to illustrate our theorems.

Development of Scoring Model on Customer Attrition Probability by Using Data Mining Techniques

  • Han, Sang-Tae;Lee, Seong-Keon;Kang, Hyun-Cheol;Ryu, Dong-Kyun
    • Communications for Statistical Applications and Methods
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    • v.9 no.1
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    • pp.271-280
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    • 2002
  • Recently, many companies have applied data mining techniques to promote competitive power in the field of their business market. In this study, we address how data mining, that is a technique to enable to discover knowledge from a deluge of data, Is used in an executed project in order to support decision making of an enterprise. Also, we develope scoring model on customer attrition probability for automobile-insurance company using data mining techniques. The development of scoring model in domestic insurance is given as an example concretely.

ANALYSIS OF THE MMPP/G/1/K QUEUE WITH A MODIFIED STATE-DEPENDENT SERVICE RATE

  • Choi, Doo Il;Kim, Bokeun;Lim, Dae-Eun
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • v.18 no.4
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    • pp.295-304
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    • 2014
  • We analyze theMMPP/G/1/K queue with a modified state-dependent service rate. The service time of customers upon service initiation is changed if the number of customers in the system reaches a threshold. Then, the changed service time is continued until the system becomes empty completely, and this process is repeated. We analyze this system using an embedded Markov chain and a supplementary variable method, and present the queue length distributions at a customer's departure epochs and then at an arbitrary time.

SOLUTIONS OF STURM-LIOUVILLE TYPE MULTI-POINT BOUNDARY VALUE PROBLEMS FOR HIGHER-ORDER DIFFERENTIAL EQUATIONS

  • Liu, Yuji
    • Journal of applied mathematics & informatics
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    • v.23 no.1_2
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    • pp.167-182
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    • 2007
  • The existence of solutions of the following multi-point boundary value problem $${x^{(n)}(t)=f(t,\;x(t),\;x'(t),{\cdots}, x^{(n-2)}(t))+r(t),\;0 is studied. Sufficient conditions for the existence of at least one solution of BVP(*) are established. It is of interest that the growth conditions imposed on f are allowed to be super-linear (the degrees of phases variables are allowed to be greater than 1 if it is a polynomial). The results are different from known ones since we don't apply the Green's functions of the corresponding problem and the method to obtain a priori bounds of solutions are different enough from known ones. Examples that can not be solved by known results are given to illustrate our theorems.

COMMON FIXED POINTS FOR WEAKENED COMPATIBLE MAPPINGS SATISFYING THE GENERALIZED ϕ-WEAK CONTRACTION CONDITION

  • Jain, Deepak;Kumar, Sanjay;Jung, Chahn Yong
    • The Pure and Applied Mathematics
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    • v.26 no.2
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    • pp.99-110
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    • 2019
  • In this paper, we prove some common fixed point theorems for pairs of weakened compatible mappings (subcompatible and occasionally weakly compatible mappings) satisfying a generalized ${\phi}-weak$ contraction condition involving various combinations of the metric functions. In fact, our results improve the results of Jain et al.. Also we provide an example for validity of our results.

DIFFERENTIAL INEQUALITIES ASSOCIATED WITH CARATHÉODORY FUNCTIONS

  • In Hwa, Kim;Nak Eun, Cho
    • Nonlinear Functional Analysis and Applications
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    • v.27 no.4
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    • pp.773-784
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    • 2022
  • The purpose of the present paper is to estimate some real parts for certain analytic functions with some applications in connection with certain integral operators and geometric properties. Also we extend some known results as special cases of main results presented here.

IMPROVING SOCIAL MEDIA DATA QUALITY FOR EFFECTIVE ANALYTICS: AN EMPIRICAL INVESTIGATION BASED ON E-BDMS

  • B. KARTHICK;T. MEYYAPPAN
    • Journal of applied mathematics & informatics
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    • v.41 no.5
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    • pp.1129-1143
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    • 2023
  • Social media platforms have become an integral part of our daily lives, and they generate vast amounts of data that can be analyzed for various purposes. However, the quality of the data obtained from social media is often questionable due to factors such as noise, bias, and incompleteness. Enhancing data quality is crucial to ensure the reliability and validity of the results obtained from such data. This paper proposes an enhanced decision-making framework based on Business Decision Management Systems (BDMS) that addresses these challenges by incorporating a data quality enhancement component. The framework includes a backtracking method to improve plan failures and risk-taking abilities and a steep optimized strategy to enhance training plan and resource management, all of which contribute to improving the quality of the data. We examine the efficacy of the proposed framework through research data, which provides evidence of its ability to increase the level of effectiveness and performance by enhancing data quality. Additionally, we demonstrate the reliability of the proposed framework through simulation analysis, which includes true positive analysis, performance analysis, error analysis, and accuracy analysis. This research contributes to the field of business intelligence by providing a framework that addresses critical data quality challenges faced by organizations in decision-making environments.