Evidence map›Paper›PMID 39341988›Full record

ArticleScientific reports2024

Design of modified long short-term memory-based zebra optimization algorithm for limiting the issue of SHEPWM in multi-level inverter.

G Krithiga, S Senthilkumar, Mohammed Alharbi, S P Mangaiyarkarasi

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

G KrithigaDepartment of Electrical and Electronics Engineering, Parisutham Institute of Technology and Science, NH 67, Ring Road, Kamaraj Nagar, Nanjikotttai, Thanjavur, 613006, India. krithiga.g2012@gmail.com.
S SenthilkumarDepartment of Electronics and Communication Engineering, E.G.S. Pillay Engineering College, Nagapattinam, Tamil Nadu, 611002, India.
Mohammed AlharbiDepartment of Electrical Engineering, College of Engineering, King Saud University, Riyadh, 11421, Saudi Arabia.
S P MangaiyarkarasiDepartment of Electrical and Electronics Engineering, University College of Engineering, Panruti Campus, Panruti, Tamil Nadu, 607106, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This research work proposes unique MLSTM-ZOA to quickly measure SAs for an MLI. Within a certain MI range, the suggested method may calculate a greater count of SAs with various solutions. Here, the main objective lies in minimizing the THD with consideration of three parameters such as MI, number of pulses per quarter cycle, and duty cycle. Furthermore, by achieving a lower fitness value in less iteration, the suggested method has definitely outperformed other methods with respect to convergence behavior, according to the data. Lastly, analysis and performance associated with the experimental validation of SHE in multi-level inverter are also carried out. The proposed MLSTM-ZOA model in terms of THD is 56.25%, 81.58%, 53.33%, and 41.67% better than MPA, HHO, MGMPA, and SF-BOA respectively. Similarly, the proposed MLSTM-ZOA model with respect to HDP is 64.03%, 47.16%, 84.01%, and 27.62% advanced than MPA, HHO, MGMPA, and SF-BOA respectively.

Indexed as

Modified long short-term memoryMulti Level InverterPulse width modulationSelective Harmonics EliminationZebra optimization algorithm

Identifiers

PMID39341988
PMCPMC11439021

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.