• 제목/요약/키워드: Value problem

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A NUMERICAL METHOD FOR THE PROBLEM OF COEFFICIENT IDENTIFICATION OF THE WAVE EQUATION BASED ON A LOCAL OBSERVATION ON THE BOUNDARY

  • Shirota, Kenji
    • Communications of the Korean Mathematical Society
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    • v.16 no.3
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    • pp.509-518
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    • 2001
  • The purpose of this paper is to propose a numerical algorithm for the problem of coefficient identification of the scalar wave equation based on a local observation on the boundary: Determine the unknown coefficient function with the knowledge of simultaneous Dirichlet and Neumann boundary values on a part of boundary. To find the unknown coefficient function, the unknown Neumann boundary value is also identified. We recast our inverse problem to variational problem. The gradient method is applied to find the minimizing functions. We confirm the effectiveness of our algorithm by numerical experiments.

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EXISTENCE OF MULTIPLE SOLUTIONS OF A SEMILINEAR BIHARMONIC PROBLEM WITH VARIABLE COEFFICIENTS

  • Jung, Tacksun;Choi, Q-Heung
    • Journal of the Chungcheong Mathematical Society
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    • v.24 no.1
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    • pp.121-130
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    • 2011
  • We obtain multiplicity results for the biharmonic problem with a variable coefficient semilinear term. We show that there exist at least three solutions for the biharmonic problem with the variable coefficient semilinear term under some conditions. We obtain this multiplicity result by applying the Leray-Schauder degree theory.

A Study on Optimization Approach for the Quantification Analysis Problem Using Neural Networks (신경회로망을 이용한 수량화 문제의 최적화 응용기법 연구)

  • Lee, Dong-Myung
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.10 no.1
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    • pp.206-211
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    • 2006
  • The quantification analysis problem is that how the m entities that have n characteristics can be linked to p-dimension space to reflect the similarity of each entity In this paper, the optimization approach for the quantification analysis problem using neural networks is suggested, and the performance is analyzed The computation of average variation volume by mean field theory that is analytical approximated mobility of a molecule system and the annealed mean field neural network approach are applied in this paper for solving the quantification analysis problem. As a result, the suggested approach by a mean field annealing neural network can obtain more optimal solution than the eigen value analysis approach in processing costs.

A Case Analysis on marital Conflict Problem and Coping Behavior -Focused on the Telephone Counsdlling- (전화 상담사례에 나타난 부부갈등문제와 대응행동)

  • 이미영
    • Journal of the Korean Home Economics Association
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    • v.33 no.1
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    • pp.141-154
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    • 1995
  • The purpose of this paper is to investigate the marital conflict problem and coping behavior. The methods of this study are quantitative and qualitative method. For the data, 1069 counselling case of the married people were collected on S counselling center in Daegu, from January to May, 1994. The results of this study are as follows: 1. The main problems are marital debauchery affairs and then the value orientation, character and communication problem in turn. 2. Most clients used the complain type as the coping gehavior. 3. Recognized problem of oneself is debauchery problem and the self-damage and immaturity. Recognized problem of spouse is husband's incapacity, debauchery and violence. alcohol problem in wife case. Recognized problem of couple is a sexual problem for the most case.

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The Possibility of Neural Network Approach to Solve Singular Perturbed Problems

  • Kim, Jee-Hyun;Cho, Young-Im
    • Journal of the Korea Society of Computer and Information
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    • v.26 no.1
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    • pp.69-76
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    • 2021
  • Recentlly neural network approach for solving a singular perturbed integro-differential boundary value problem have been researched. Especially the model of the feed-forward neural network to be trained by the back propagation algorithm with various learning algorithms were theoretically substantiated, and neural network models such as deep learning, transfer learning, federated learning are very rapidly evolving. The purpose of this paper is to study the approaching method for developing a neural network model with high accuracy and speed for solving singular perturbed problem along with asymptotic methods. In this paper, we propose a method that the simulation for the difference between result value of singular perturbed problem and unperturbed problem by using neural network approach equation. Also, we showed the efficiency of the neural network approach. As a result, the contribution of this paper is to show the possibility of simple neural network approach for singular perturbed problem solution efficiently.

A novel approach for the design of multi-class reentrant manufacturing systems

  • Yoo, Dong-Joon;Jung, Jae-Hak;Lee, In-Beum;Lee, Euy-Soo;Yi, Gyeong-beom
    • 제어로봇시스템학회:학술대회논문집
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    • 2004.08a
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    • pp.710-715
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    • 2004
  • The design problem of manufacturing system is addressed, adopting the closed queueing network model with multiple loops and re-entrant flows. The entire design problem is divided into two hierarchical sub-problems of (1) determining the station configuration and (2) optimizing the lot constitution; then they are tackled by neighbor search algorithm (NSA) and greedy mean value analysis (GMVA), respectively. Unlike the conventional MVA concerning multi-class closed queueing networks, the GMVA doesn't stick to a fixed lot proportion; rather it tries to find the optimal balance. The NSA, on the other hand, improves the object function value by altering the station configuration successively with its superior neighbor. The moderate time complexity, presented in big-${o}$ notation, enables us to apply the method even to the large-size practical cases, and the CPU time of an enlarged problem can be approximated by the same equation. The validity of our analytic approach is backed up by simulation studies with a widespread simulation package.

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Linear Bottleneck Assignment Problem Based on Reverse-delete Algorithm (선형 병목할당 문제의 역-삭제 알고리즘)

  • Lee, Sang-Un
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.13 no.6
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    • pp.211-220
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    • 2013
  • This paper proposes an algorithm that easily finds an optimal solution for linear bottleneck assignment problems. It is either threshold or augmenting path algorithm that is generally used to solve the bottleneck assignment problem. This paper proposes a reverse-delete algorithm that follows 2 steps. Firstly, the algorithm deletes the maximum cost in a given matrix until it renders a single row or column. Next, the algorithm improves any solution that contains a cost exceeding the threshold value $c^*_{ij}$. Upon its application to 28 balanced assignment problems and 7 unbalanced problems, the algorithm is found to be both successful and simple.

Optimal Pricing Design Based on Preference Values of Purchasing Restrictions for Tour Products (여행상품 구매조건의 선호가치에 따른 최적 여행상품 가격설계 연구)

  • Hwang, Myung Sun;Kim, Su Young;Yoon, Moon Gil
    • Korean Management Science Review
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    • v.31 no.1
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    • pp.27-40
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    • 2014
  • Tour products have been recognized as a perishable asset. For tour operation companies (TOCs), improving profitability is a core decision problem for their business. Since package tour products, typical products of TOCs, are perishable after the tour was departed, TOCs have been tried to increase their sales before the departure date with various marketing strategies including price discounts. The pricing problem for perishable assets have been studied in Revenue Management for a long time. However, it is hard to find a research on pricing decisions for tour products. In this paper, we focus on a pricing problem for tour products. In particular, we will consider the pricing scheme with customer preference values on purchasing conditions. With conjoint analysis, we can use the part-worth value as a preference value for each level of purchasing conditions. To construct various discount prices, we use an enumeration method and suggest a mathematical optimization model. With experimental analysis for a sample tour package, we will show that our pricing process is very helpful for designing customer-oriented pricing decision.

Intelligent Route Construction Algorithm for Solving Traveling Salesman Problem

  • Rahman, Md. Azizur;Islam, Ariful;Ali, Lasker Ershad
    • International Journal of Computer Science & Network Security
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    • v.21 no.4
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    • pp.33-40
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    • 2021
  • The traveling salesman problem (TSP) is one of the well-known and extensively studied NPC problems in combinatorial optimization. To solve it effectively and efficiently, various optimization algorithms have been developed by scientists and researchers. However, most optimization algorithms are designed based on the concept of improving route in the iterative improvement process so that the optimal solution can be finally found. In contrast, there have been relatively few algorithms to find the optimal solution using route construction mechanism. In this paper, we propose a route construction optimization algorithm to solve the symmetric TSP with the help of ratio value. The proposed algorithm starts with a set of sub-routes consisting of three cities, and then each good sub-route is enhanced step by step on both ends until feasible routes are formed. Before each subsequent expansion, a ratio value is adopted such that the good routes are retained. The experiments are conducted on a collection of benchmark symmetric TSP datasets to evaluate the algorithm. The experimental results demonstrate that the proposed algorithm produces the best-known optimal results in some cases, and performs better than some other route construction optimization algorithms in many symmetric TSP datasets.

The Numerical Solution of Time-Optimal Control Problems by Davidenoko's Method (Davidenko법에 의한 시간최적 제어문제의 수치해석해)

  • Yoon, Joong-sun
    • Journal of the Korean Society for Precision Engineering
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    • v.12 no.5
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    • pp.57-68
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    • 1995
  • A general procedure for the numerical solution of coupled, nonlinear, differential two-point boundary-value problems, solutions of which are crucial to the controller design, has been developed and demonstrated. A fixed-end-points, free-terminal-time, optimal-control problem, which is derived from Pontryagin's Maximum Principle, is solved by an extension of Davidenko's method, a differential form of Newton's method, for algebraic root finding. By a discretization process like finite differences, the differential equations are converted to a nonlinear algebraic system. Davidenko's method reconverts this into a pseudo-time-dependent set of implicitly coupled ODEs suitable for solution by modern, high-performance solvers. Another important advantage of Davidenko's method related to the time-optimal problem is that the terminal time can be computed by treating this unkown as an additional variable and sup- plying the Hamiltonian at the terminal time as an additional equation. Davidenko's method uas used to produce optimal trajectories of a single-degree-of-freedom problem. This numerical method provides switching times for open-loop control, minimized terminal time and optimal input torque sequences. This numerical technique could easily be adapted to the multi-point boundary-value problems.

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