Traffic Anomaly Detection in Wireless Sensor Networks Based on Principal Component Analysis and Deep Convolution Neural Network

Research article (IEEE Access, 2022) · cited 55× · AI/ML
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Traffic Anomaly Detection in Wireless Sensor Networks Based on Principal Component Analysis and Deep Convolution Neural Network

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Traffic Anomaly Detection in Wireless Sensor Networks Based on Principal Component Analysis and Deep Convolution Neural Network is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). Traffic Anomaly Detection in Wireless Sensor Networks Based on Principal Component Analysis and Deep Convolution Neural Network. Retrieved May 24, 2026, from https://4ort.xyz/entity/traffic-anomaly-detection-in-wireless-sensor-networks-based-on-principal-component-analysis-and-deep-convolution-neural-
MLA “Traffic Anomaly Detection in Wireless Sensor Networks Based on Principal Component Analysis and Deep Convolution Neural Network.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/traffic-anomaly-detection-in-wireless-sensor-networks-based-on-principal-component-analysis-and-deep-convolution-neural-.
BibTeX @misc{4ortxyz_traffic-anomaly-detection-in-wireless-sensor-networks-based-on-principal-component-analysis-and-deep-convolution-neural-_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Traffic Anomaly Detection in Wireless Sensor Networks Based on Principal Component Analysis and Deep Convolution Neural Network}}, year = {2026}, url = {https://4ort.xyz/entity/traffic-anomaly-detection-in-wireless-sensor-networks-based-on-principal-component-analysis-and-deep-convolution-neural-}, note = {Accessed: 2026-05-24}}
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