• Title/Summary/Keyword: problem solving approach

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ENHANCED SEMI-ANALYTIC METHOD FOR SOLVING NONLINEAR DIFFERENTIAL EQUATIONS OF FRACTIONAL ORDER

  • JANG, BONGSOO;KIM, HYUNJU
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • v.23 no.4
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    • pp.283-300
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    • 2019
  • In this paper, we propose a new semi-analytic approach based on the generalized Taylor series for solving nonlinear differential equations of fractional order. Assuming the solution is expanded as the generalized Taylor series, the coefficients of the series can be computed by solving the corresponding recursive relation of the coefficients which is generated by the given problem. This method is called the generalized differential transform method(GDTM). In several literatures the standard GDTM was applied in each sub-domain to obtain an accurate approximation. As noticed in [19], however, a direct application of the GDTM in each sub-domain loses a term of memory which causes an inaccurate approximation. In this work, we derive a new recursive relation of the coefficients that reflects an effect of memory. Several illustrative examples are demonstrated to show the effectiveness of the proposed method. It is shown that the proposed method is robust and accurate for solving nonlinear differential equations of fractional order.

Designing an Instructional Model for Smart Technology-Enhanced Team-Based Learning (스마트 테크놀로지를 활용한 팀 기반 학습 모형 설계 연구)

  • Lee, Soo-Young
    • Journal of The Korean Association of Information Education
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    • v.17 no.4
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    • pp.497-506
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    • 2013
  • The purpose of this study is to explore and develop a new instructional approach to a technology-enhanced, collaborative learning environment called Smart technology-enhanced Team-Based Learning (S-TBL). We designed a novel instructional model that combines mobile technology, collaborative teamwork, a problem-solving process, and a variety of evaluation techniques from the viewpoint of a conventional team-based model. Based on the traditional TBL model, we have integrated smart learning technologies: 1) to provide a holistic learning environment that integrates learning resources, assessment tools, and problem solving spaces; and 2) to enhance collaboration and communication between team members and between an instructor and his or her students. The S-TBL instructional approach combines: 1) individual learning and collaborative team learning; 2) conceptual learning and problem-solving & critical thinking; 3) both individual and group assessment; 4) self-directed learning and teacher-led instruction; and 5) personal reflection and publication.

A Hybrid Heuristic Approach for Supply Chain Planningwith n Multi-Level Multi-Item Capacitated Lot Sizing Model (자원제약하의 다단계 다품목 공급사슬망 생산계획을 위한 휴리스틱 알고리즘)

  • Shin Hyun-Joon
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.7 no.1
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    • pp.89-95
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    • 2006
  • Planning distributed manufacturing logistics is one of main issues in supply chain management. This paper proposes a hybrid heuristic approach for the Multi-Level, multi-item Capacitated Lot Sizing Problem (MLCLSP) in supply chain network. MLCLSP corresponds to a mixed integer programming (MIP) problem. With integer variable solutions determined by heuristic search, this MIP problem becomes linear program (LP). By repeatedly solving the relaxed MIP problems with a heuristic search method in a hybrid manner, this proposed approach allocates finite manufacturing resources fur each distributed facilities and generates feasible production plans. Meta heuristic search algorithm is presented to solve the MIP problems. The experimental test evaluates the computational performance under a variety of problem scenarios.

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Fuzzy Decision Making System

  • Karpovsky, Ephim Ja
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1993.06a
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    • pp.806-809
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    • 1993
  • This paper focuses on the usage of the fuzzy set theory in decision making systems. The approach to calculation of generalized membership function, based on application of method of principal components is proposed. For solving of the problem of fuzzy forecasting the development of Bayes procedure is used. The structure of decision making system, in which following procedures are fulfilled, is discussed.

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Experience of Cognitive-Behavioral Treatment for Patients with Chronic Headache (만성두통 환자에 대한 인지행동치료경험)

  • Koh, Kyung-Bong
    • Korean Journal of Psychosomatic Medicine
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    • v.4 no.1
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    • pp.85-90
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    • 1996
  • Cognitive-behavioral approach to two cases with chronic headache was presented. Cognitive-behavioral interventions focus on indirectly altering symptom-related physiological activity by changing the way patients cope with headache-eliciting stressors. This treatment focuses directly on the patients' cognitive and behavioral changes. Cognitive-behavioral treatment can be divided into three phases Education, self-monitoring, and problem-solving or coping-skills training. Literature reviews on the follow-up evaluation of therapeutic effectiveness revealed that cognitive-behavioral treatment is effective in the management of chronic headache.

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Direct Numerical Simulation of Active Fiber Composite (능동 섬유 복합재의 직접적 수치 모사)

  • 백승훈;김승조
    • Proceedings of the Korean Society For Composite Materials Conference
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    • 2003.04a
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    • pp.5-9
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    • 2003
  • Stress and deflection of Active Fiber Composite(AFC) embedded and/or attached composite structures are numerically investigated at the constituent level by the Direct Numerical Simulation(DNS). The DNS approach which models and simulates the fiber and matrix directly using 3D finite elements need to be solved by efficient way. To handle this large scale problem, parallel program for solving piezoelectric behavior was developed and run on the parallel computing environment. Also, the stress result from DNS approach is compared with that from uniform field model.

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Applying CBR for Default Risk Forecasting (채무불이행위험의 예측을 위한 CBR응용)

  • Kim Jin-Baek
    • Management & Information Systems Review
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    • v.3
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    • pp.179-199
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    • 1999
  • Case-Based Reasoning(CBR) offers a new approach for developing knowledge based systems. In case-based approach the problem solving experience of the domain expert is encoded in the form of cases. CBR has successfully been applied to many kinds of problems such as design, planning, diagnosis and forecasting. In this paper, CBR was applied for forecasting default risk. The applied result was successful in spite of the small casebase. Generally, CBR requires large casebase. So, if the number of data was large, the result was better. But in this paper, what financial variable was more forecastable was not tested. Next, this should be tested.

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Stereopsis with cellular neural networks (국소적인 연결을 갖는 신경회로망을 이용한 스테레오 정합)

  • 박성진;채수익
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.31B no.12
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    • pp.124-131
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    • 1994
  • In this paper, we propose a new approach of solving the stereopsis problem with a discrete-time cellular neural network(DTCNN) where each node has connections only with its local neithbors. Because the matching process of stereo correspondence depends on its geometrically local characteristics, the DTCNN is suitable for the stereo correspondence. Moreover, it can be easily implemented in VLSI. Therefore, we employed a two-layer DTCNN with dual templates, which are determined with the back propagation learning rule. Based on evaluation of the proposed approach for several random-dot stereograms, its performance is better than that of the Marr-Poggio algorithm.

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A Route-Splitting Approach to the Vehicle Routing Problem (차량경로문제의 경로분할모형에 관한 연구)

  • Kang, Sung-Min
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2005.10a
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    • pp.57-78
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    • 2005
  • The vehicle routing problem (VRP) is to determine a set of feasible vehicle routes, one for each vehicle, such that each customer is visited exactly once and the total distance travelled by the vehicles is minimized. A feasible route is defined as a simple circuit including the depot such that the total demand of the customers in the route does not exceed the vehicle capacity. While there have been significant advances recently in exact solution methodology, the VRP is not a well solved problem. We find most approaches still relying on the branch and bound method. These approaches employ various methodologies to compute a lower bound on the optimal value. We introduce a new modelling approach, termed route-splitting, for the VRP that allows us to address problems whose size is beyond the current computational range of set-partitioning models. The route-splitting model splits each vehicle route into segments, and results in more tractable subproblems. Lifting much of the burden of solving combinatorially hard subproblems, the route-splitting approach puts more weight on the LP master problem, Recent breakthroughs in solving LP problems (Nemhauser, 1994) bode well for our approach. Lower bounds are computed on five symmetric VRPs with up to 199 customers, and eight asymmetric VRPs with up to 70 customers. while it is said that the exact methods developed for asymmetric instances have in general a poor performance when applied to symmetric ones (Toth and Vigo, 2002), the route splitting approach shows a competent performance of 93.5% on average in the symmetric VRPs. For the asymmetric ones, the approach comes up with lower bounds of 97.6% on average. The route-splitting model can deal with asymmetric cost matrices and non-identical vehicles. Given the ability of the route-splitting model to address a wider range of applications and its good performance on asymmetric instances, we find the model promising and valuable for further research.

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