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Relevant bibliographies by topics / Curve fitting technique

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Journal articles

Academic literature on the topic 'Curve fitting technique'

Author: Grafiati

Published: 14 April 2023

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Journal articles on the topic "Curve fitting technique"

1

Rajan, T. S., and S. Narayanaswamy. "A novel curve fitting technique applied to drying curves." Canadian Journal of Chemical Engineering 64, no. 6 (1986): 1033–34. http://dx.doi.org/10.1002/cjce.5450640624.

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2

Damos, Diane L. "Determining Transfer of Training Using Curve Fitting." Proceedings of the Human Factors Society Annual Meeting 32, no. 18 (1988): 1276–79. http://dx.doi.org/10.1177/154193128803201818.

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The purpose of this paper is to demonstrate the measurement of learning and transfer using a curve-fitting technique discussed in a 1985 Human Factors article by Spears. The data were collected during an experiment that determined if rotation skills could become automated with practice and if the skills could transfer between stimuli. The dependent variables of interest were the slope and intercept of the regression equation relating correct reaction time and degrees of rotation. Curve fitting was accomplished using a common statistical package, BMDP, and an IBM-XT. The curve-fitting technique

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3

Zehr, E. P., and M. Klimstra. "The reliability of a curve fitting technique for Hoffmann-reflex recruitment curve analysis." Journal of Biomechanics 39 (January 2006): S483—S484. http://dx.doi.org/10.1016/s0021-9290(06)84975-4.

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4

Motlagh, O., S. H. Tang, M. N. Maslan, Fairul Azni Jafar, and Maslita A. Aziz. "A novel graph computation technique for multi-dimensional curve fitting." Connection Science 25, no. 2-3 (2013): 129–38. http://dx.doi.org/10.1080/09540091.2013.851173.

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5

Hsieh, Hsun-Chang, and Wen-Tong Chang. "Virtual knot technique for curve fitting of rapidly varying data." Computer Aided Geometric Design 11, no. 1 (1994): 71–95. http://dx.doi.org/10.1016/0167-8396(94)90025-6.

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6

Hyun, Seokjeong, and Cheol Kim. "An efficient shape-preserving curve fitting technique for complex structures." Communications in Numerical Methods in Engineering 20, no. 9 (2004): 737–46. http://dx.doi.org/10.1002/cnm.693.

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7

Xianping, Tu, Lei Xianqing, Ma Wensuo, Wang Xiaoyi, Hu Luqing, and Zuo Xiaolin. "The minimum zone fitting and error evaluation for the logarithmic curve based on geometry optimization approximation algorithm." Transactions of the Institute of Measurement and Control 41, no. 15 (2019): 4380–86. http://dx.doi.org/10.1177/0142331219858855.

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The minimum zone fitting and error evaluation for the logarithmic curve has important applications. Based on geometry optimization approximation algorithm whilst considering geometric characteristics of logarithmic curves, a new fitting and error evaluation method for the logarithmic curve is presented. To this end, two feature points, to serve as reference, are chosen either from those located on the least squares logarithmic curve or from amongst measurement points. Four auxiliary points surrounding each of the two reference points are then arranged to resemble vertices of a square. Subseque

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8

Ray, Aditi, Joydipta Banerjee, T. R. G. Kutty, Arun Kumar, and Srikumar Banerjee. "Construction of master sintering curve of ThO2 pellets using optimization technique." Science of Sintering 44, no. 2 (2012): 147–60. http://dx.doi.org/10.2298/sos1202147r.

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Sintering kinetics and densification behavior of pure ThO2 have been studied using high temperature dilatometer experiments at constant rate of heating. Sintering activation energy has been determined by Wang and Raj method. Master sintering curve (MSC) for densification is a functional sintering model that describes densification under arbitrary time temperature excursion of a particular material during sintering. MSC for pure ThO2 has been constructed by fitting experimental relative density versus work of sintering data with modified sigmoid function. Five independent parameters of the fitt

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9

Holler, Farida, David H. Burns, and James B. Callis. "Direct Use of Second Derivatives in Curve-Fitting Procedures." Applied Spectroscopy 43, no. 5 (1989): 877–82. http://dx.doi.org/10.1366/0003702894202292.

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Most curve-fitting procedures deal with an unknown, variable baseline by modeling it with a function involving a number of parameters. In view of the facts that (1) there is often no analytically relevant information in the baseline, and (2) there is usually no functional form known, a priori, for the baseline, we have chosen to eliminate it by means of the second-derivative transformation. The resulting profile is deconvoluted by fitting it with the second derivative of the sum of an appropriate number of component curves. The utility of this procedure is demonstrated on simulated data with t

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10

Tang, Xiao-Ming, Chen Li, and Douglas J. Patterson. "A curve-fitting technique for determining dispersion characteristics of guided elastic waves." GEOPHYSICS 75, no. 3 (2010): E153—E160. http://dx.doi.org/10.1190/1.3420736.

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We have developed a novel curve-fitting method to estimate dispersion characteristics of guided elastic waves and investigate its application to field wireline and logging while drilling (LWD) acoustic data processing. In an elastic waveguide such as a fluid-filled borehole with a logging tool, the frequency dispersion of a guided-wave mode is characterized by a monotonically varying dispersion curve bounded by its low- and high-frequency limits. The detailed behavior of the curves relates to various elastic/acoustic parameters of the complicated waveguide structure. The novelty of the propose

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