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regression algorithm

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Series: ASM Handbook
Volume: 21
Publisher: ASM International
Published: 01 January 2001
DOI: 10.31399/asm.hb.v21.a0003386
EISBN: 978-1-62708-195-5
... of the mechanics based model, the regression algorithm, and the semi-empirical analysis. composites damage tolerance military aircraft metallic structures composite structures regression algorithm durability semi-empirical analysis THE DAMAGE TOLERANCE DESIGN PHILOSOPHY has been required on all...
Series: ASM Handbook
Volume: 22A
Publisher: ASM International
Published: 01 December 2009
DOI: 10.31399/asm.hb.v22a.a0005407
EISBN: 978-1-62708-196-2
... particular combination of database distribution, architecture, training algorithm, and transfer function can be tested by an analysis of the network response in a form of linear regression between network outputs (predictions) and corresponding targets (experimental data) for the training and testing...
Series: ASM Handbook
Volume: 24A
Publisher: ASM International
Published: 30 June 2023
DOI: 10.31399/asm.hb.v24A.a0006994
EISBN: 978-1-62708-439-0
... Abstract Process optimization is the discipline of adjusting a process to optimize a specified set of parameters without violating engineering constraints. This article reviews data-driven optimization methods based on genetic algorithms and stochastic models and demonstrates their use...
Series: ASM Handbook
Volume: 20
Publisher: ASM International
Published: 01 January 1997
DOI: 10.31399/asm.hb.v20.a0002476
EISBN: 978-1-62708-194-8
... for tensile strength. It reviews life prediction reliability models used for predicting the life of a component with complex geometry and loading. The article outlines reliability algorithms and presents several applications to illustrate the utilization of these reliability algorithms in structural...
Series: ASM Handbook
Volume: 24A
Publisher: ASM International
Published: 30 June 2023
DOI: 10.31399/asm.hb.v24A.a0006975
EISBN: 978-1-62708-439-0
... applications to date corresponds to supervised learning. In this case, a set of input variables (e.g., laser power and travel velocity) is associated with a labeled response variable (e.g., measured porosity). In regression, the algorithm would be used to predict the percentage porosity for a new set...
Series: ASM Handbook
Volume: 4F
Publisher: ASM International
Published: 01 February 2024
DOI: 10.31399/asm.hb.v4F.a0007017
EISBN: 978-1-62708-450-5
... for a wide variety of standard SAE-grade steels. Subsequently, Siebert et al. ( Ref 17 ) and Brooks ( Ref 18 ) implemented multiple regression algorithms to refine Just’s original regression analysis for hardenability estimation. The equations developed by Brooks are listed in Table 3 . It is important...
Series: ASM Handbook
Volume: 24
Publisher: ASM International
Published: 15 June 2020
DOI: 10.31399/asm.hb.v24.a0006568
EISBN: 978-1-62708-290-7
... friction, φ, is the angle that the yield locus (least-squares linear regression fit of the shear stress data points) makes with the horizontal axis. Cohesion, C , is the point at which the yield locus crosses the vertical axis. Unconfined yield strength, σ c , is the nonzero intersection...
Series: ASM Handbook
Volume: 4A
Publisher: ASM International
Published: 01 August 2013
DOI: 10.31399/asm.hb.v04a.a0005796
EISBN: 978-1-62708-165-8
... content increased, their effect on hardenability decreased. Results of Just's hardenability predictions were in good agreement with measurements for a wide variety of standard SAE-grade steels. Implementation of multiple regression algorithms was conducted by other investigators. Siebert et al. ( Ref...
Series: ASM Handbook
Volume: 24A
Publisher: ASM International
Published: 30 June 2023
DOI: 10.31399/asm.hb.v24A.a0006968
EISBN: 978-1-62708-439-0
... (MJ), and sheet lamination (SL). It presents the benefits of online monitoring and process control for polymer AM. It also introduces the respective monitoring devices used, including the models and algorithms designed for polymer AM online monitoring and control. additive manufacturing binder...
Series: ASM Handbook
Volume: 22B
Publisher: ASM International
Published: 01 November 2010
DOI: 10.31399/asm.hb.v22b.a0005544
EISBN: 978-1-62708-197-9
.... LAMMPS features parallelism via a spatial decomposition algorithm; short-range pairwise Lennard-Jones and Coulombic interactions; long-range Coulombic interactions via Ewald or particle-mesh Ewald; harmonic molecular potentials; class II molecular potentials; NVE, NVT, and NPT dynamics; constraints...
Series: ASM Handbook
Volume: 19
Publisher: ASM International
Published: 01 January 1996
DOI: 10.31399/asm.hb.v19.a0002369
EISBN: 978-1-62708-193-1
... , given by the equation (Eq 2) N = C S − b This assumes that the curve will be a straight line on a log-log plot. C is called the S - N coefficient and b is the exponent, which is one over the slope of the curve. The median line can be determined by a linear regression...
Series: ASM Handbook
Volume: 11A
Publisher: ASM International
Published: 30 August 2021
DOI: 10.31399/asm.hb.v11A.a0006803
EISBN: 978-1-62708-329-4
..., are the question to be answered, the computational effort is even greater. Efficient gradient-based numerical algorithms for estimating probabilities of failure ( Ref 9 – 11 ) were developed through the 1980s, but all suffer from the problem of being restricted to computationally efficient models, or using...
Series: ASM Handbook
Volume: 22B
Publisher: ASM International
Published: 01 November 2010
DOI: 10.31399/asm.hb.v22b.a0005534
EISBN: 978-1-62708-197-9
... of sequential experimentation. An orthogonal design is one in which the input variables are uncorrelated, and the regression coefficients of the fitted linear model are also uncorrelated ( Ref 13 ). More information about orthogonality and flexibility follows. Fractional Factorial Design The size...
Series: ASM Handbook
Volume: 4A
Publisher: ASM International
Published: 01 August 2013
DOI: 10.31399/asm.hb.v04a.a0005814
EISBN: 978-1-62708-165-8
... a regression line, as shown in Fig. 9(a) . A measure of the goodness of a linear regression is the coefficient of determination ( R 2 ); if its value is close to 1, then there is a strong linear relationship between the dependent and independent variables. In the context of Fig. 9(a) the value of R 2...
Series: ASM Handbook
Volume: 22B
Publisher: ASM International
Published: 01 November 2010
DOI: 10.31399/asm.hb.v22b.a0005540
EISBN: 978-1-62708-197-9
... and springback analysis: the type of solution algorithm/governing equation and the type of element. The article provides information on various models for material yield criteria. finite element methods friction sheet metal forming springback analysis SOFTWARE PROGRAMS continue to provide...
Series: ASM Handbook
Volume: 17
Publisher: ASM International
Published: 01 August 2018
DOI: 10.31399/asm.hb.v17.a0006439
EISBN: 978-1-62708-190-0
... by technical device tradeoffs. Random noise, so-called white noise, is caused by stray electrons. Those are influenced by heat differences on the sensor and other physical effects. Additionally, several image processing algorithms also cause noise. Dark noise is caused by the lack of illumination...
Book Chapter

By S. Lampman
Series: ASM Handbook
Volume: 10
Publisher: ASM International
Published: 15 December 2019
DOI: 10.31399/asm.hb.v10.a0006645
EISBN: 978-1-62708-213-6
Series: ASM Handbook
Volume: 24A
Publisher: ASM International
Published: 30 June 2023
DOI: 10.31399/asm.hb.v24A.a0006978
EISBN: 978-1-62708-439-0
.... Intentional data-reduction methods, such as lowering capture rates and number of channels (e.g., single-wavelength photodiodes versus wide spectrometers), can mitigate some of these challenges. Statistical Process Control Detection using statistical image-processing algorithms is preferred for most...
Series: ASM Handbook
Volume: 17
Publisher: ASM International
Published: 01 August 2018
DOI: 10.31399/asm.hb.v17.a0006463
EISBN: 978-1-62708-190-0
... observed between nondestructive testing signal magnitude and crack size in automated eddy current bolt hole inspections by the United States Air Force. POD, probability of detection These types of data are well suited to regression analysis, and this approach to POD estimation was documented...
Series: ASM Handbook
Volume: 17
Publisher: ASM International
Published: 01 August 2018
DOI: 10.31399/asm.hb.v17.a0006438
EISBN: 978-1-62708-190-0
.... Visual image processing algorithms designed to detect subtle differences between a reference part image and an inspection object or between images of a part taken after a time interval looking for indications of change. The primary guiding principle of any inspection whether it is well addressed...