Support vector regression optimized by black widow optimization algorithm combining with feature selection by MARS for mining blast vibration prediction

Xu, Guoquan; Wang, Xinyu

doi:10.1016/j.measurement.2023.113106

Cited by 10 publications

(2 citation statements)

References 70 publications

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“…As a component of the strategies related to movement, the spider's motions within the web are simulated using linear and spiral patterns, as outlined in Equation ( 3) and depicted in Figure 5 [39][40][41].…”

Section: Movementmentioning

confidence: 99%

The Optimization of a Pipeline Temperature Monitoring Method Based on Non-Local Means with the Black Widow Optimization Algorithm

Lou,

Wang,

Sima

et al. 2023

Energies

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The accuracy of pipeline temperature monitoring using the Brillouin Optical Time Domain Analysis system depends on the Brillouin Gain Spectrum in the Brillouin Optical Time Domain Analysis system. The Non-Local Means noise reduction algorithm, due to its ability to use the data patterns available within the two-dimensional measurement data space, has been used to improve the Brillouin Gain Spectrum in the Brillouin Optical Time Domain Analysis system. This paper studies a new Non-Local Means algorithm optimized through the Black Widow Optimization Algorithm, in view of the unreasonable selection of smoothing parameters in other Non-Local Means algorithms. The field test demonstrates that, the new algorithm, when compared to other Non-Local Means methods, excels in preserving the detailed information within the Brillouin Gain Spectrum. It successfully restores the fundamental shape and essential characteristics of the Brillouin Gain Spectrum. Notably, at the 25 km fiber end, it achieves a 3 dB higher Signal-to-Noise Ratio compared to other Non-Local Means noise reduction algorithms. Furthermore, the Brillouin Gain Spectrum values exhibit increases of 9.4% in Root Mean Square Error, 12.5% in Sum of Squares Error, and 10% in Full Width at Half Maximum. The improved method has a better denoising effect and broad application prospects in pipeline safety.

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Section: Movementmentioning

confidence: 99%

The Optimization of a Pipeline Temperature Monitoring Method Based on Non-Local Means with the Black Widow Optimization Algorithm

Lou,

Wang,

Sima

et al. 2023

Energies

View full text Add to dashboard Cite

show abstract

“…The predictions resulted in reliable results. Xu [ 35 ] proposed an integration modeling method for predicting PPV and frequency based on multivariate adaptive regression splines (MARS), support vector regression (SVR), and black widow optimization algorithm (BWOA). The research results indicate that this method is a promising tool for predicting blasting vibrations.…”

Section: Introductionmentioning

confidence: 99%