• Title/Summary/Keyword: problem analysis

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An analytical solution for compaction grouting problem considering exothermic temperature effect of slurry

  • Chao Li;Yingke Liu;Man Yuan;Tengrui Yang
    • Geomechanics and Engineering
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    • v.35 no.6
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    • pp.593-601
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    • 2023
  • In this paper, an analytical solution of large-strain cylindrical cavity expansion in compaction grouting problem under temperature field is given. Considering the stress increment caused by temperature, the analytical solution of cavity expansion under traditional isothermal conditions is improved by substituting the temperature stress increment into the cavity expansion analysis. Subsequently, combined with the first law of thermodynamics, the energy theory is also introduced into the cylindrical cavity expansion analysis, and the energy dissipation solution of cylindrical cavity expansion is derived. Finally, the validity and reliability of solution are proved by comparing the results of expansion pressure with those in published literatures. The results show that the dimensionless expansion pressure increases with the increase of temperature, and the thermal response increases with the increase of dilation angle. The higher the exothermic temperature of grouting slurry, the greater the plastic deformation energy of the surrounding soil, that is, the greater the influence on the surrounding soil deformation and the surrounding environment. The proposed solution not only enrich the theoretical system of cavity expansion, but also can be used as a theoretical tool for energy geotechnical engineering problems, such as CPT, nuclear waste disposal, energy pile and chemical grouting, etc.

A Novel and Effective University Course Scheduler Using Adaptive Parallel Tabu Search and Simulated Annealing

  • Xiaorui Shao;Su Yeon Lee;Chang Soo Kim
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.18 no.4
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    • pp.843-859
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    • 2024
  • The university course scheduling problem (UCSP) aims at optimally arranging courses to corresponding rooms, faculties, students, and timeslots with constraints. Previously, the university staff solved this thorny problem by hand, which is very time-consuming and makes it easy to fall into chaos. Even some meta-heuristic algorithms are proposed to solve UCSP automatically, while most only utilize one single algorithm, so the scheduling results still need improvement. Besides, they lack an in-depth analysis of the inner algorithms. Therefore, this paper presents a novel and practical approach based on Tabu search and simulated annealing algorithms for solving USCP. Firstly, the initial solution of the UCSP instance is generated by one construction heuristic algorithm, the first fit algorithm. Secondly, we defined one union move selector to control the moves and provide diverse solutions from initial solutions, consisting of two changing move selectors. Thirdly, Tabu search and simulated annealing (SA) are combined to filter out unacceptable moves in a parallel mode. Then, the acceptable moves are selected by one adaptive decision algorithm, which is used as the next step to construct the final solving path. Benefits from the excellent design of the union move selector, parallel tabu search and SA, and adaptive decision algorithm, the proposed method could effectively solve UCSP since it fully uses Tabu and SA. We designed and tested the proposed algorithm in one real-world (PKNU-UCSP) and ten random UCSP instances. The experimental results confirmed its effectiveness. Besides, the in-depth analysis confirmed each component's effectiveness for solving UCSP.

The Comparison of Neural Network Learning Paradigms: Backpropagation, Simulated Annealing, Genetic Algorithm, and Tabu Search

  • Chen Ming-Kuen
    • Proceedings of the Korean Society for Quality Management Conference
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    • 1998.11a
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    • pp.696-704
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    • 1998
  • Artificial neural networks (ANN) have successfully applied into various areas. But, How to effectively established network is the one of the critical problem. This study will focus on this problem and try to extensively study. Firstly, four different learning algorithms ANNs were constructed. The learning algorithms include backpropagation, simulated annealing, genetic algorithm, and tabu search. The experimental results of the above four different learning algorithms were tested by statistical analysis. The training RMS, training time, and testing RMS were used as the comparison criteria.

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Theoretical analysis of composite beams under uniformly distributed load

  • Daouadji, Tahar Hassaine;Adim, Belkacem
    • Advances in materials Research
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    • v.5 no.1
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    • pp.1-9
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    • 2016
  • The bending problem of a functionally graded cantilever beam subjected to uniformly distributed load is investigated. The material properties of the functionally graded beam are assumed to vary continuously through the thickness, according to a power-law distribution of the volume fraction of the constituents. First, the partial differential equation, which is satisfied by the stress functions for the axisymmetric deformation problem is derived. Then, stress functions are obtained by proper manipulation. A practical example is presented to show the application of the method.

Analysis on Point Projection onto Curves (점의 곡선위 직교투영에 대한 분석)

  • Ko, Kwang Hee
    • Korean Journal of Computational Design and Engineering
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    • v.18 no.1
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    • pp.49-57
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    • 2013
  • In this paper, orthogonal projection of a point onto a 2D planar curve is discussed. The problem is formulated as finding a point on a curve where the tangent of the curve is perpendicular to the vector connecting the point on the curve and a point in the space. Existing methods are compared and novel approaches to solve the problem are presented. The proposed methods are tested with examples.

Application of Multi Criteria Decision Making for Selection of Automobile Safety Option (안전 옵션 선정 다준규의사결정 모델)

  • Kim, Taehee
    • Journal of Auto-vehicle Safety Association
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    • v.10 no.2
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    • pp.50-55
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    • 2018
  • Choosing automobile safety options is price-performance matter. The best fit options to buyer who has a certain driving habit are problem of MCDM (Multi Criteria Decision Making) because price of safety option, statistics of relating accident, consequence of accident, and driving habit are the multi criteria to be evaluated. In this paper, PROMETHEE-GAIA methodology is applied for solving this MCDM problem. The result shows that a different driving habit makes different choosing priority of safety options.

A Study for the Improvement of the Brake Squeal Noise (제동시 브레이크 소음 개선에 관한 연구)

  • 김동우;이희욱
    • Transactions of the Korean Society of Automotive Engineers
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    • v.4 no.6
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    • pp.223-228
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    • 1996
  • The frequency of the brake squeal noise can be changed during braking, and this frequency shifting is due to variation of braking deceleration rate. The natural frequency of the brake system also shifted according to deceleration rate. It makes difficult to treat this problem. This paper shows an experimental study on the brake squeal noise having main frequencies of about 450~500Hz. And it shows how to improve the brake squeal noise problem.

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Sliding Manifold Tuning Method Using Wavelet Neural Network (웨이브릿 신경회로망을 활용한 슬라이딩 매니폴드 조정기법)

  • 홍석우;전홍태
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2000.11a
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    • pp.195-198
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    • 2000
  • Sliding mode control method is popularly used for robustness to distrurbance and variance of systems internal parameter. However, one of the serious problem of this method is Chattering which occurs in neighborhood of sliding manifold. Another problem is that we cannot expect robustness before system starts sliding mode. A new tuning method of sliding manifold which changes the parameter of sliding manifold dynamically using Wavelet Neural Network is proposed in this paper. We can expect the better performance in sliding mode control by the wavelet neural networks excellent property of approximating arbitrary function for multi-resolution analysis and decrease chattering drastically.

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Neural Networks Analysis of Transferring Students

  • Kim, Tae-Yoon;Lee, Ji-Young;Song, Kyu-Moon
    • Journal of the Korean Data and Information Science Society
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    • v.14 no.1
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    • pp.11-21
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    • 2003
  • In 1997 a new educational system that allows student to transfer between and within universities was first introduced. As a result, most colleges of basic arts and sciences face a serious problem since quite a few students there have transferred or seems to want to transfer. In this paper we study a problem of building a forecasting neural network for students who can possibly transfer.

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Analytic Method on Fuzzy Goal Programming Problem

  • Hong, Dug-Hun;Kim, Kyung-Tae
    • Journal of the Korean Data and Information Science Society
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    • v.17 no.2
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    • pp.599-607
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    • 2006
  • We propose a simple new analytic method for solving a fuzzy goal programming (FGP) problem with general membership functions of fuzzy goals and re-examine a previously defined method for dealing with fuzzy weights for each of the goals. Several illustrative examples are given.

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