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A novel approach to gas turbine fault diagnosis based on learning of fault characteristic maps using hybrid residual compensation extreme learning machine-growing neural gas model
Research article (Journal of the Brazilian Society of Mechanical Sciences and Engineering, 2021) · cited 14× · AI/ML
A novel approach to gas turbine fault diagnosis based on learning of fault characteristic maps using hybrid residual compensation extreme learning machine-growing neural gas model
Summary
A novel approach to gas turbine fault diagnosis based on learning of fault characteristic maps using hybrid residual compensation extreme learning machine-growing neural gas model is a scholarly article[1].
Key Facts
A novel approach to gas turbine fault diagnosis based on learning of fault characteristic maps using hybrid residual compensation extreme learning machine-growing neural gas model's instance of is recorded as scholarly article[2].
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APA4ort.xyz Knowledge Graph. (2026). A novel approach to gas turbine fault diagnosis based on learning of fault characteristic maps using hybrid residual compensation extreme learning machine-growing neural gas model. Retrieved May 24, 2026, from https://4ort.xyz/entity/a-novel-approach-to-gas-turbine-fault-diagnosis-based-on-learning-of-fault-characteristic-maps-using-hybrid-residual-com
MLA“A novel approach to gas turbine fault diagnosis based on learning of fault characteristic maps using hybrid residual compensation extreme learning machine-growing neural gas model.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/a-novel-approach-to-gas-turbine-fault-diagnosis-based-on-learning-of-fault-characteristic-maps-using-hybrid-residual-com.
BibTeX@misc{4ortxyz_a-novel-approach-to-gas-turbine-fault-diagnosis-based-on-learning-of-fault-characteristic-maps-using-hybrid-residual-com_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{A novel approach to gas turbine fault diagnosis based on learning of fault characteristic maps using hybrid residual compensation extreme learning machine-growing neural gas model}}, year = {2026}, url = {https://4ort.xyz/entity/a-novel-approach-to-gas-turbine-fault-diagnosis-based-on-learning-of-fault-characteristic-maps-using-hybrid-residual-com}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): A novel approach to gas turbine fault diagnosis based on learning of fault characteristic maps using hybrid residual compensation extreme learning machine-growing neural gas model — https://4ort.xyz/entity/a-novel-approach-to-gas-turbine-fault-diagnosis-based-on-learning-of-fault-characteristic-maps-using-hybrid-residual-com (retrieved 2026-05-24)
