• 제목/요약/키워드: Minimum Feature Variables

검색결과 9건 처리시간 0.028초

조립품을 위한 비선형 공차할당 (Nonlinear Tolerance Allocation for Assembly Components)

  • 김광수;최후곤
    • 산업공학
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    • 제16권spc호
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    • pp.39-44
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    • 2003
  • As one of many design variables, the role of dimension tolerances is to restrict the amount of size variation in a manufactured feature while ensuring functionality. In this study, a nonlinear integer model has been modeled to allocate the optimal tolerance to each individual feature at a minimum manufacturing cost. While a normal distribution determines statistically worst tolerances with its symmetrical property in many previous tolerance allocation studies, a asymmetrical distribution is more realistic because its mean is not always coincident with a process center. A nonlinear integer model is modeled to allocate the optimal tolerance to a feature based on a beta distribution at a minimum total cost. The total cost as a function of tolerances is defined by machining cost and quality loss. After the convexity of manufacturing cost is checked by the Hessian matrix, the model is solved by the Complex Method. Finally, a numerical example is presented demonstrating successful model implementation for a nonlinear design case.

Runoff Prediction from Machine Learning Models Coupled with Empirical Mode Decomposition: A case Study of the Grand River Basin in Canada

  • Parisouj, Peiman;Jun, Changhyun;Nezhad, Somayeh Moghimi;Narimani, Roya
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2022년도 학술발표회
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    • pp.136-136
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    • 2022
  • This study investigates the possibility of coupling empirical mode decomposition (EMD) for runoff prediction from machine learning (ML) models. Here, support vector regression (SVR) and convolutional neural network (CNN) were considered for ML algorithms. Precipitation (P), minimum temperature (Tmin), maximum temperature (Tmax) and their intrinsic mode functions (IMF) values were used for input variables at a monthly scale from Jan. 1973 to Dec. 2020 in the Grand river basin, Canada. The support vector machine-recursive feature elimination (SVM-RFE) technique was applied for finding the best combination of predictors among input variables. The results show that the proposed method outperformed the individual performance of SVR and CNN during the training and testing periods in the study area. According to the correlation coefficient (R), the EMD-SVR model outperformed the EMD-CNN model in both training and testing even though the CNN indicated a better performance than the SVR before using IMF values. The EMD-SVR model showed higher improvement in R value (38.7%) than that from the EMD-CNN model (7.1%). It should be noted that the coupled models of EMD-SVR and EMD-CNN represented much higher accuracy in runoff prediction with respect to the considered evaluation indicators, including root mean square error (RMSE) and R values.

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서식지 특성에 따른 맹꽁이 개체수와 기상요인과의 관계 분석 (Relationship between Abundances of Kaloula borealis and Meteorological Factors based on Habitat Features)

  • 노백호
    • 한국환경복원기술학회지
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    • 제19권3호
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    • pp.103-119
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    • 2016
  • This study aims to assess habitat feature on the large-scale spawning ground of the Boreal Digging Frog Kaloula borealis in Daemyung retarding basin of Daegu, and to analyze the relationships between species abundance and meteorological factors for each habitat. Fifty-seven(57) pitfalls were installed to collect species abundance of 4 survey regions, and high-resolution satellite image, soil sampling equipment, digital topographic map, and GPS were used to develop habitat features such as terrain, soil, vegetation, human disturbance. The analysis shows that the frog is most abundant in sloped region with densely herbaceous cover in southern part of the retarding basin. In the breeding season, lowland regions, where Phragmites communis and P. japonica dominant wetlands and temporary ponds distributed, are heavily concentrated by the species for spawning and foraging. Located in between legally protected Dalsung wetands and lowland regions of the retarding basin, riverine natural levee is ecologically important area as core habitat for Kaloula borealis, and high number of individuals were detected both breeding and non-breeding seasons. Temperate- and pressure-related meteorological elements are selected as statistically significant variables in species abundance of non-breeding season in lowland and highland regions. However, in sloped regions, only a few variables are statistically significant during non-breeding season. Moreover, breeding activities in sloped regions are statistically significant with minimum temperature, grass minimum temperature, dew point temperature, and vapor pressure. Significant meteorological factors with habitat features are effectively applied to establish species conservation strategy of the retarding basin and to construct for avoiding massive road-kills on neighboring roads of the study sites, particularly post-breeding movements from spawning to burrowing areas.

구조체의 위상학적 최적화를 위한 비선형 프로그래밍 (NLP Formulation for the Topological Structural Optimization)

  • Bark, Jaihyeong;Omar N. Ghattas;Lee, Li-Hyung
    • 한국전산구조공학회:학술대회논문집
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    • 한국전산구조공학회 1996년도 봄 학술발표회 논문집
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    • pp.182-189
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    • 1996
  • The focus of this study is on the problem of the design of structure of undetermined topology. This problem has been regarded as being the most challenging of structural optimization problems, because of the difficulty of allowing topology to change. Conventional approaches break down when element sizes approach to zero, due to stiffness matrix singularity. In this study, a novel nonlinear Programming formulation of the topology Problem is developed and examined. Its main feature is the ability to account for topology variation through zero element sizes. Stiffness matrix singularity is avoided by embedding the equilibrium equations as equality constraints in the optimization problem. Although the formulation is general, two dimensional plane elasticity examples are presented. The design problem is to find minimum weight of a plane structure of fixed geometry but variable topology, subject to constraints on stress and displacement. Variables are thicknesses of finite elements, and are permitted to assume zero sizes. The examples demonstrate that the formulation is effective for finding at least a locally minimal weight.

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솔레노이드 액추에이터의 비선형 동적응답에 대한 구조최적설계 (Structural Optimization for Nonlinear Dynamic Response of Solenoid Actuator)

  • 백석흠;김현수;장득열;이승범;권영석;노의동;이창훈
    • 한국자동차공학회논문집
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    • 제21권1호
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    • pp.113-120
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    • 2013
  • This paper proposes a design optimization approach for core of solenoid actuators by combining optimization techniques with the finite element method (FEM). A solenoid is an important element part which hydraulically controls a transmission system, etc. The demanded feature of the solenoid is that it performs an electromagnetic force output being constant regardless of the stroke and being proportional to coil current. The plunger compresses a spring with a minimum force of 12 N over an 1.7 mm travel. The orthogonal array, analysis of variance (ANOVA) techniques and response surface optimization, are employed to determine the main effects and their optimal design variables. The methodology is demonstrated as a optimization tool for the core design of a solenoid actuator.

텐서플로우 튜토리얼 방식의 머신러닝 신규 모델 개발 : 캐글 타이타닉 데이터 셋을 중심으로 (Developing of New a Tensorflow Tutorial Model on Machine Learning : Focusing on the Kaggle Titanic Dataset)

  • 김동길;박용순;박래정;정태윤
    • 대한임베디드공학회논문지
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    • 제14권4호
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    • pp.207-218
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    • 2019
  • The purpose of this study is to develop a model that can systematically study the whole learning process of machine learning. Since the existing model describes the learning process with minimum coding, it can learn the progress of machine learning sequentially through the new model, and can visualize each process using the tensor flow. The new model used all of the existing model algorithms and confirmed the importance of the variables that affect the target variable, survival. The used to classification training data into training and verification, and to evaluate the performance of the model with test data. As a result of the final analysis, the ensemble techniques is the all tutorial model showed high performance, and the maximum performance of the model was improved by maximum 5.2% when compared with the existing model using. In future research, it is necessary to construct an environment in which machine learning can be learned regardless of the data preprocessing method and OS that can learn a model that is better than the existing performance.

Research on Selecting Influential Climatic Factors and Optimal Timing Exploration for a Rice Production Forecast Model Using Weather Data

  • Jin-Kyeong Seo;Da-Jeong Choi;Juryon Paik
    • 한국컴퓨터정보학회논문지
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    • 제28권7호
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    • pp.57-65
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    • 2023
  • 쌀 생산량 예측의 정확성을 높이기 위한 대다수의 연구는 모델의 정확도 증진에 초점이 맞춰져 있다. 이에 비해, 예측 모델을 적용할 대상 데이터 자체에 관한 연구는 상대적으로 미흡하다. 쌀 생산량 데이터에 동일한 종속변수와 예측 모델을 사용하여 다른 특성들로 구성된 두 부류의 데이터에 적용하면, 결과의 차이가 발생하는데 이때 어느 데이터 셋이 더 우수한지 판단하기는 어려운 일이다. 이러한 문제를 해결하기 위해, 예측 모델 적용 전에 데이터 내에서 예측 결과에 큰 영향을 미칠 가능성이 있는 특성들을 선별하고, 이를 중심으로 모델링을 수행하면, 데이터의 구성이 다르더라도 안정적인 예측 결과를 얻을 수 있을 것이다. 본 연구에서는 기상청의 종관기상관측(ASOS) 데이터를 활용하여, 쌀 생산량의 안정적이고 일관된 예측을 위해 데이터 구성 특성들의 조정을 통해 최적의 기반 변수를 선별하는 방법에 대해 제안한다. 본 연구의 결과는 향후 다른 연구에서 성능평가의 유용성을 높이는 데 기여할 것으로 기대한다.

구조체의 위상학적 최적화를 위한 비선형 프로그래밍 (A Nonlinear Programming Formulation for the Topological Structural Optimization)

  • 박재형;이리형
    • 전산구조공학
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    • 제9권3호
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    • pp.169-177
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    • 1996
  • 구조물에 있어서 위상학적 최적화 문제는 최적화를 구하는 과정에서 구조체가 변화함으로 인한 어려움 때문에 최적화 분야에서 가장 어려운 문제로 간주되어 왔다. 종래의 방법으로는 일반적으로 구조요소 사이즈가 영으로 접근할 때 강성 매트릭스의 singularity를 발생시킴으로써 최적의 해를 얻지 못하고 도중에 계산이 종료되어 버린다. 본 연구에 있어서는 이러한 문제점들을 해결하기 위한 비선형 프로그래밍 formulation을 제안하는 것을 목적으로 한다. 이 formulation의 주된 특성은 요소 사이즈가 영이 되는 것을 허용한다. 평형방정식을 등제약조건으로 간주함으로써 강성 매트릭스의 singularity를 피할 수 있다. 이 formulation을 하중을 받는 구조물에 있어서 응력과 변위의 제약조건하에서 중량을 최소화할때의 유한요소의 두께를 구하는 디자인 문제에 적용하여, 이 formulation이 위상학적 최적화에 있어서의 효과를 입증하였다.

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Cylindrical bending of multilayered composite laminates and sandwiches

  • Sayyad, Atteshamuddin S.;Ghugal, Yuwaraj M.
    • Advances in aircraft and spacecraft science
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    • 제3권2호
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    • pp.113-148
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    • 2016
  • In a whole variety of higher order plate theories existing in the literature no consideration is given to the transverse normal strain / deformation effects on flexural response when these higher order theories are applied to shear flexible composite plates in view of minimizing the number of unknown variables. The objective of this study is to carry out cylindrical bending of simply supported laminated composite and sandwich plates using sinusoidal shear and normal deformation plate theory. The most important feature of the present theory is that it includes the effects of transverse normal strain/deformation. The displacement field of the presented theory is built upon classical plate theory and uses sine and cosine functions in terms of thickness coordinate to include the effects of shear deformation and transverse normal strain. The theory accounts for realistic variation of the transverse shear stress through the thickness and satisfies the shear stress free conditions at the top and bottom surfaces of the plate without using the problem dependent shear correction factor. Governing equations and boundary conditions of the theory are obtained using the principle of minimum potential energy. The accuracy of the proposed theory is examined for several configurations of laminates under various static loadings. Some problems are presented for the first time in this paper which can become the base for future research. For the comparison purpose, the numerical results are also generated by using higher order shear deformation theory of Reddy, first-order shear deformation plate theory of Mindlin and classical plate theory. The numerical results show that the present theory provides displacements and stresses very accurately as compared to those obtained by using other theories.