Evaluation of an Approximate Channel-Base Current and Its Analytical Function Parameters Based on the Measured Lightning Magnetic Field

Ramarao, Gandi; Chandrasekaran, K.

doi:10.1109/temc.2018.2879541

Cited by 5 publications

(2 citation statements)

References 42 publications

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“…As a representative optimization algorithm in swarm intelligence, the Particle Swarm Optimization (PSO) algorithm has the characteristics of parallel processing and good robustness in selecting optimal parameters [28][29][30][31][32]. Besides, it can find the global optimal solution to a problem with a high probability, and its computational efficiency is higher than of the traditional stochastic algorithms.…”

Section: Introductionmentioning

confidence: 99%

“…Besides, it can find the global optimal solution to a problem with a high probability, and its computational efficiency is higher than of the traditional stochastic algorithms. Consequently, it has been used in remote sensing image classification parameter optimization [28], wind forecasting model optimization [29], and medical model optimization [30,31].…”

Section: Introductionmentioning

confidence: 99%

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Particle Swarm Optimization-Based Noise Filtering Algorithm for Photon Cloud Data in Forest Area

et al. 2019

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The Ice, Cloud, and land Elevation Satellite-2 (ICESat-2), which is equipped with the Advanced Topographic Laser Altimeter System (ATLAS), was launched successfully in 15 September 2018. The ATLAS represents a micro-pulse photon-counting laser system, which is expected to provide more comprehensive and scientific data for carbon storage. However, the ATLAS system is sensitive to the background noise, which poses a tremendous challenge to the photon cloud noise filtering. Moreover, the Density Based Spatial Clustering of Applications with Noise (DBSCAN) is a commonly used algorithm for noise removal from the photon cloud but there has not been an in-depth study on its parameter selection yet. This paper presents an automatic photon cloud filtering algorithm based on the Particle Swarm Optimization (PSO) algorithm, which can be used to optimize the two key parameters of the DBSCAN algorithm instead of using the manual parameter adjustment. The Particle Swarm Optimization Density Based Spatial Clustering of Applications with Noise (PSODBSCAN) algorithm was tested at different laser intensities and laser pointing types using the MATLAS dataset of the forests located in Virginia, East Coast, and the West Coast, USA. The results showed that the PSODBSCAN algorithm and the localized statistical algorithm were effective in identifying the background noise and preserving the signal photons in the raw MATLAS data. Namely, the PSODBSCAN achieved the mean F value of 0.9759, and the localized statistical algorithm achieved the mean F value of 0.6978. For both laser pointing types and laser intensities, the proposed algorithm achieved better results than the localized statistical algorithm. Therefore, the PSODBSCAN algorithm could support the MATLAS photon cloud data noise filtering applicably without manually selecting parameters.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Particle Swarm Optimization-Based Noise Filtering Algorithm for Photon Cloud Data in Forest Area

et al. 2019

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Segmentation and characteristic extraction for Schumann Resonance transient events

2022

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Evaluation Of Lightning Current Parameters Using Measured Lightning Induced Voltage On Distribution Power Lines

Izadi

Kadir

Osman

2019

2019 11th Asia-Pacific International Conference on Lightning (APL)

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In this paper, an algorithm had been proposed to evaluate the lightning current parameters using measured voltage from overhead distribution lines based on lightning location obtained from lightning location system. Moreover, the performance of algorithm had been considered using different samples of induced voltage. The results showed that the proposed algorithm could determine the lightning current parameters in an acceptable accuracy range. The proposed method is based on the measured values of lightning induced voltage as collecting this parameter is easier and more accessible than electromagnetic field components that had been widely used in past researches.

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Evaluation of an Approximate Channel-Base Current and Its Analytical Function Parameters Based on the Measured Lightning Magnetic Field

Cited by 5 publications

References 42 publications

Particle Swarm Optimization-Based Noise Filtering Algorithm for Photon Cloud Data in Forest Area

Particle Swarm Optimization-Based Noise Filtering Algorithm for Photon Cloud Data in Forest Area

Segmentation and characteristic extraction for Schumann Resonance transient events

Evaluation Of Lightning Current Parameters Using Measured Lightning Induced Voltage On Distribution Power Lines

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