Use of PSO to determine lightning channel‐base‐current function parameters for standard severe negative first and subsequent return stroke approximation

Ramarao, Gandi; Chandrasekaran, K.

doi:10.1049/iet-smt.2018.5320

Cited by 4 publications

(2 citation statements)

References 23 publications

(36 reference statements)

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“…From the research practice, we found that in a short time series of 20 µs, the sum of two Heidler functions (formula 7) can be used to construct the return stroke current, and a group of parameters can be found by the PSO algorithm that can reconstruct the current waveform accurately to a certain extent [20], [40]. However, as described in Section 4.1, the construction method of the sum of the two groups of functions is not suitable for the waveform reconstruction of a lightning return-stroke current with a long time series.…”

Section: B Constructor Of a Long Time-series Triggered Lightning Retmentioning

confidence: 99%

Parametric Reconstruction Method for the Long Time-Series Return-Stroke Current of Triggered Lightning Based on the Particle Swarm Optimization Algorithm

et al. 2020

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The lightning research group of the Chinese Academy of Meteorological Sciences has carried out observations and experiments with artificially triggered lightning for more than ten years, and it accumulated thousands of examples of channel base current data on the return stroke of artificially triggered lightning prior to 2020. Based on the current data, this paper explores ways of improving the constructed function of a long time-series (400) return stroke and the parametric reconstruction of the current waveform. The long time-series current can be divided into three components: the breakdown pulse current, corona current and quasi-uniform current. The corona current and quasi-uniform current are constructed by a Heidler function, while the breakdown pulse current is determined by the waveform characteristics of the current peak, which can be divided into the Heidler type and high-order exponential type. According to the three-component model of the return-stroke current, a two-step parametric reconstruction method for the long time-series lightning return-stroke current based on the particle swarm optimization (PSO) algorithm is proposed. In this paper, the results of the parameterized reconstruction of 14 return strokes are given, and the results of the multidimensional error analysis of 13 long time-series return strokes are given to illustrate the accuracy of the improved parameterized model of the return-stroke current and the effectiveness of the two-step reconstruction method based on the PSO algorithm.

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Section: B Constructor Of a Long Time-series Triggered Lightning Retmentioning

confidence: 99%

Parametric Reconstruction Method for the Long Time-Series Return-Stroke Current of Triggered Lightning Based on the Particle Swarm Optimization Algorithm

et al. 2020

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“…Among these methods, particle swarm optimization (PSO) is a simple yet powerful optimization algorithm and has been applied to numerous applications in various fields of science and engineering, such as machine learning, image processing, data mining operation research, etc. [9][10][11][12][13][14][15][16][17][18][19]. However, PSO has some characteristics that, in some sense and to a certain extent, have some similarity to those found in other populationbased computational models, such as genetic algorithms (GAs) and other evolutionary computing techniques.…”

Section: Introductionmentioning

confidence: 99%

Cross-Correlation Wavelet-Domain-Based Particle Swarm Optimization for Lightning Mapping

et al. 2021

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Several processing methods have been proposed for estimating the real pattern of the temporal location and spatial map of the lightning strikes. However, due to the complexity of lightning signals, providing accurate lightning maps estimation remains a challenging task. This paper presents a cross-correlation wavelet-domain-based particle swarm optimization (CCWD-PSO) technique for an accurate and robust representation of lightning mapping. The CCWD method provides an initial estimate of the lightning map, while the PSO attempts to optimize the trajectory of the lightning map by finding the optimal sliding window of the cross-correlation. The technique was further enhanced through the introduction of a novel lightning event extraction method that enables faster processing of the lightning mapping. The CCWD-PSO method was validated and verified using three narrow bipolar events (NBEs) flashes. The observed results demonstrate that this technique offers high accuracy in representing the real lightning mapping with low estimation errors.

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Modeling of line impedance stabilization network impedance characteristic based on genetic algorithm

Zhu

Zhao

Yan

et al. 2021

Microelectronics Journal

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Use of PSO to determine lightning channel‐base‐current function parameters for standard severe negative first and subsequent return stroke approximation

Cited by 4 publications

References 23 publications

Parametric Reconstruction Method for the Long Time-Series Return-Stroke Current of Triggered Lightning Based on the Particle Swarm Optimization Algorithm

Parametric Reconstruction Method for the Long Time-Series Return-Stroke Current of Triggered Lightning Based on the Particle Swarm Optimization Algorithm

Cross-Correlation Wavelet-Domain-Based Particle Swarm Optimization for Lightning Mapping

Modeling of line impedance stabilization network impedance characteristic based on genetic algorithm

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