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Deep Subdomain Learning Adaptation Network: A Sensor Fault-Tolerant Soft Sensor for Industrial Processes

Research article (IEEE Transactions on Neural Networks and Learning Systems, 2022) · cited 26× · AI/ML
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Deep Subdomain Learning Adaptation Network: A Sensor Fault-Tolerant Soft Sensor for Industrial Processes

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Deep Subdomain Learning Adaptation Network: A Sensor Fault-Tolerant Soft Sensor for Industrial Processes is a scholarly article[1].

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  • Deep Subdomain Learning Adaptation Network: A Sensor Fault-Tolerant Soft Sensor for Industrial Processes's instance of is recorded as scholarly article[2].

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APA 4ort.xyz Knowledge Graph. (2026). Deep Subdomain Learning Adaptation Network: A Sensor Fault-Tolerant Soft Sensor for Industrial Processes. Retrieved May 24, 2026, from https://4ort.xyz/entity/deep-subdomain-learning-adaptation-network-a-sensor-fault-tolerant-soft-sensor-for-industrial-processes
MLA “Deep Subdomain Learning Adaptation Network: A Sensor Fault-Tolerant Soft Sensor for Industrial Processes.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/deep-subdomain-learning-adaptation-network-a-sensor-fault-tolerant-soft-sensor-for-industrial-processes.
BibTeX @misc{4ortxyz_deep-subdomain-learning-adaptation-network-a-sensor-fault-tolerant-soft-sensor-for-industrial-processes_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Deep Subdomain Learning Adaptation Network: A Sensor Fault-Tolerant Soft Sensor for Industrial Processes}}, year = {2026}, url = {https://4ort.xyz/entity/deep-subdomain-learning-adaptation-network-a-sensor-fault-tolerant-soft-sensor-for-industrial-processes}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Deep Subdomain Learning Adaptation Network: A Sensor Fault-Tolerant Soft Sensor for Industrial Processes — https://4ort.xyz/entity/deep-subdomain-learning-adaptation-network-a-sensor-fault-tolerant-soft-sensor-for-industrial-processes (retrieved 2026-05-24)

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