Boosting the Performance of Genetic Algorithms for Variable Selection in Partial Least Squares Spectral Calibrations.

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Boosting the Performance of Genetic Algorithms for Variable Selection in Partial Least Squares Spectral Calibrations.

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2017 nî lūn-bûn

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2017年の論文

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2017年論文

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2017年論文

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2017年論文

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2017年論文

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Boosting the Performance of Ge ...... Squares Spectral Calibrations.

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Boosting the Performance of Ge ...... Squares Spectral Calibrations.

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Boosting the Performance of Ge ...... Squares Spectral Calibrations.

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P1476

Boosting the Performance of Ge ...... Squares Spectral Calibrations.

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P2093

Barry K Lavine

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Collin G White

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P2860

Wavelength interval selection in multicomponent spectral analysis by moving window partial least-squares regression with applications to mid-infrared and near-infrared spectroscopic data.

Pattern recognition analysis of differential mobility spectra with classification by chemical family.

Genetic algorithms in chemistry.

Variables selection methods in near-infrared spectroscopy.

Multiarray sensors with pattern recognition for the detection, classification, and differentiation of bacteria at subspecies and strain levels.

Genetic algorithm-based method for selecting wavelengths and model size for use with partial least-squares regression: application to near-infrared spectroscopy.

Selection method of quasi-continuous wavelength combination with applications to the near-infrared spectroscopic analysis of soil organic matter.

Wavelength selection for multivariate calibration using tikhonov regularization.

Detection and identification of bacteria using antibiotic susceptibility and a multi-array electrochemical sensor with pattern recognition.

Theoretical Justification of Wavelength Selection in PLS Calibration: Development of a New Algorithm.

P304

2092-2101

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P31

scholarly article

P356

10.1177/0003702817713501

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P433

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P478

http://www.w3.org/2001/XMLSchema#string

P577

2017-01-01T00:00:00Z

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P698

28537475

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