A feature extraction and deep learning approach for network traffic volume prediction considering detector reliability

Research article (Computer-Aided Civil and Infrastructure Engineering, 2023) · cited 20× · AI/ML
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A feature extraction and deep learning approach for network traffic volume prediction considering detector reliability

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A feature extraction and deep learning approach for network traffic volume prediction considering detector reliability is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). A feature extraction and deep learning approach for network traffic volume prediction considering detector reliability. Retrieved May 24, 2026, from https://4ort.xyz/entity/a-feature-extraction-and-deep-learning-approach-for-network-traffic-volume-prediction-considering-detector-reliability
MLA “A feature extraction and deep learning approach for network traffic volume prediction considering detector reliability.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/a-feature-extraction-and-deep-learning-approach-for-network-traffic-volume-prediction-considering-detector-reliability.
BibTeX @misc{4ortxyz_a-feature-extraction-and-deep-learning-approach-for-network-traffic-volume-prediction-considering-detector-reliability_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{A feature extraction and deep learning approach for network traffic volume prediction considering detector reliability}}, year = {2026}, url = {https://4ort.xyz/entity/a-feature-extraction-and-deep-learning-approach-for-network-traffic-volume-prediction-considering-detector-reliability}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): A feature extraction and deep learning approach for network traffic volume prediction considering detector reliability — https://4ort.xyz/entity/a-feature-extraction-and-deep-learning-approach-for-network-traffic-volume-prediction-considering-detector-reliability (retrieved 2026-05-24)

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