Utilization of genetic algorithms to optimize Eucalyptus globulus pulp yield models based on NIR spectra

Ho, Tu X.; Schimleck, Laurence R.; Sinha, Arijit

doi:10.1007/s00226-021-01272-y

Cited by 5 publications

(1 citation statement)

References 32 publications

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“…If the threshold value is too large, some valid feature information may be eliminated, while some invalid information and noise may be introduced if the threshold value is too small. In this study, a genetic algorithm (GA) [36] was used for threshold optimization. The initial population number was set to 50, the chromosome binary code length was set to 20, the maximum evolutionary algebra was set to 100, the crossover probability was set to 0.8, and the mutation probability was set to 0.1.…”

Section: Determination Of the Optimal Threshold Of Safs With Genetic ...mentioning

confidence: 99%

Algorithm of Stability-Analysis-Based Feature Selection for NIR Calibration Transfer

Zhang

et al. 2022

Sensors

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For conventional near-infrared spectroscopy (NIR) technology, even within the same sample, the NIR spectral signal can vary significantly with variation of spectrometers and the spectral collection environment. In order to improve the applicability and application of NIR prediction models, effective calibration transfer is essential. In this study, a stability-analysis-based feature selection algorithm (SAFS) for NIR calibration transfer is proposed, which is used to extract effective spectral band information with high stability between the master and slave instruments during the calibration transfer process. The stability of the spectrum bands shared between the master and slave instruments is used as the evaluation index, and the genetic algorithm was used to select suitable thresholds to filter out the spectral feature information suitable for calibration transfer. The proposed SAFS algorithm was applied to two near-infrared datasets of corn oil content and larch wood density. Simultaneously, its calibration transfer performances were compared with two classical feature selection methods. The effects of different preprocessing algorithms and calibration transfer algorithms were also assessed. The model with the feature variables selected by the SAFS obtained the best prediction. The SAFS algorithm can simplify the spectral data to be transferred and improve the transfer efficiency, and the universality of the SAFS allows it to be used to optimize calibration transfer in various situations. By combining different preprocessing and classic feature selection methods with this, the sensitivity of the correlation between spectral data and component information are improved significantly, as well as the effect of calibration transfer, which will be deeply developed.

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Section: Determination Of the Optimal Threshold Of Safs With Genetic ...mentioning

confidence: 99%

Algorithm of Stability-Analysis-Based Feature Selection for NIR Calibration Transfer

Zhang

et al. 2022

Sensors

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Utilization of genetic algorithms to optimize loblolly pine wood property models based on NIR spectra and SilviScan data

Schimleck

Dahlen

et al. 2022

Wood Sci Technol

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On the selection of the weighting parameter value in optimizing Eucalyptus globulus pulp yield models based on NIR spectra

Roberts

et al. 2022

Wood Sci Technol

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Utilization of genetic algorithms to optimize Eucalyptus globulus pulp yield models based on NIR spectra

Cited by 5 publications

References 32 publications

Algorithm of Stability-Analysis-Based Feature Selection for NIR Calibration Transfer

Algorithm of Stability-Analysis-Based Feature Selection for NIR Calibration Transfer

Utilization of genetic algorithms to optimize loblolly pine wood property models based on NIR spectra and SilviScan data

On the selection of the weighting parameter value in optimizing Eucalyptus globulus pulp yield models based on NIR spectra

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