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WSAFormer-DFFN: A model for rotating machinery fault diagnosis using 1D window-based multi-head self-attention and deep feature fusion network
Research article (Engineering Applications of Artificial Intelligence, 2023) · cited 54× · AI/ML
WSAFormer-DFFN: A model for rotating machinery fault diagnosis using 1D window-based multi-head self-attention and deep feature fusion network
Summary
WSAFormer-DFFN: A model for rotating machinery fault diagnosis using 1D window-based multi-head self-attention and deep feature fusion network is a scholarly article[1].
Key Facts
WSAFormer-DFFN: A model for rotating machinery fault diagnosis using 1D window-based multi-head self-attention and deep feature fusion network's instance of is recorded as scholarly article[2].
References
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Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). WSAFormer-DFFN: A model for rotating machinery fault diagnosis using 1D window-based multi-head self-attention and deep feature fusion network. Retrieved May 24, 2026, from https://4ort.xyz/entity/wsaformer-dffn-a-model-for-rotating-machinery-fault-diagnosis-using-1d-window-based-multi-head-self-attention-and-deep-f
MLA“WSAFormer-DFFN: A model for rotating machinery fault diagnosis using 1D window-based multi-head self-attention and deep feature fusion network.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/wsaformer-dffn-a-model-for-rotating-machinery-fault-diagnosis-using-1d-window-based-multi-head-self-attention-and-deep-f.
BibTeX@misc{4ortxyz_wsaformer-dffn-a-model-for-rotating-machinery-fault-diagnosis-using-1d-window-based-multi-head-self-attention-and-deep-f_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{WSAFormer-DFFN: A model for rotating machinery fault diagnosis using 1D window-based multi-head self-attention and deep feature fusion network}}, year = {2026}, url = {https://4ort.xyz/entity/wsaformer-dffn-a-model-for-rotating-machinery-fault-diagnosis-using-1d-window-based-multi-head-self-attention-and-deep-f}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): WSAFormer-DFFN: A model for rotating machinery fault diagnosis using 1D window-based multi-head self-attention and deep feature fusion network — https://4ort.xyz/entity/wsaformer-dffn-a-model-for-rotating-machinery-fault-diagnosis-using-1d-window-based-multi-head-self-attention-and-deep-f (retrieved 2026-05-24)
