A distributed anomaly detection model for wireless sensor networks based on the one-class principal component classifier
Summary
A distributed anomaly detection model for wireless sensor networks based on the one-class principal component classifier is a scholarly article[1].
Key Facts
A distributed anomaly detection model for wireless sensor networks based on the one-class principal component classifier's instance of is recorded as scholarly article[2].
References
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APA4ort.xyz Knowledge Graph. (2026). A distributed anomaly detection model for wireless sensor networks based on the one-class principal component classifier. Retrieved May 24, 2026, from https://4ort.xyz/entity/a-distributed-anomaly-detection-model-for-wireless-sensor-networks-based-on-the-one-class-principal-component-classifier
MLA“A distributed anomaly detection model for wireless sensor networks based on the one-class principal component classifier.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/a-distributed-anomaly-detection-model-for-wireless-sensor-networks-based-on-the-one-class-principal-component-classifier.
BibTeX@misc{4ortxyz_a-distributed-anomaly-detection-model-for-wireless-sensor-networks-based-on-the-one-class-principal-component-classifier_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{A distributed anomaly detection model for wireless sensor networks based on the one-class principal component classifier}}, year = {2026}, url = {https://4ort.xyz/entity/a-distributed-anomaly-detection-model-for-wireless-sensor-networks-based-on-the-one-class-principal-component-classifier}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): A distributed anomaly detection model for wireless sensor networks based on the one-class principal component classifier — https://4ort.xyz/entity/a-distributed-anomaly-detection-model-for-wireless-sensor-networks-based-on-the-one-class-principal-component-classifier (retrieved 2026-05-24)
