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Optimised approach of feature selection based on genetic and binary state transition algorithm in the classification of bearing fault in BLDC motor
Research article (IET Electric Power Applications, 2020) · cited 17× · AI/ML
Optimised approach of feature selection based on genetic and binary state transition algorithm in the classification of bearing fault in BLDC motor
Summary
Optimised approach of feature selection based on genetic and binary state transition algorithm in the classification of bearing fault in BLDC motor is a scholarly article[1].
Key Facts
Optimised approach of feature selection based on genetic and binary state transition algorithm in the classification of bearing fault in BLDC motor's instance of is recorded as scholarly article[2].
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APA4ort.xyz Knowledge Graph. (2026). Optimised approach of feature selection based on genetic and binary state transition algorithm in the classification of bearing fault in BLDC motor. Retrieved May 24, 2026, from https://4ort.xyz/entity/optimised-approach-of-feature-selection-based-on-genetic-and-binary-state-transition-algorithm-in-the-classification-of-
MLA“Optimised approach of feature selection based on genetic and binary state transition algorithm in the classification of bearing fault in BLDC motor.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/optimised-approach-of-feature-selection-based-on-genetic-and-binary-state-transition-algorithm-in-the-classification-of-.
BibTeX@misc{4ortxyz_optimised-approach-of-feature-selection-based-on-genetic-and-binary-state-transition-algorithm-in-the-classification-of-_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Optimised approach of feature selection based on genetic and binary state transition algorithm in the classification of bearing fault in BLDC motor}}, year = {2026}, url = {https://4ort.xyz/entity/optimised-approach-of-feature-selection-based-on-genetic-and-binary-state-transition-algorithm-in-the-classification-of-}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Optimised approach of feature selection based on genetic and binary state transition algorithm in the classification of bearing fault in BLDC motor — https://4ort.xyz/entity/optimised-approach-of-feature-selection-based-on-genetic-and-binary-state-transition-algorithm-in-the-classification-of- (retrieved 2026-05-24)
