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Design of a pollution ontology-based event generation framework for the dynamic application of traffic restrictions

Authors: David Eneko Ruiz de Gauna; Luis Enrique Sánchez; Almudena Ruiz-Iniesta;

Design of a pollution ontology-based event generation framework for the dynamic application of traffic restrictions

Abstract

Madrid City Data 2022 (District 1 and 4) Weather data (weather_data_2022.csv) Air Quality Data (aq_data_2022.csv) Traffic Data (traffic_data_2022.csv) Calendar Data (date_data_2022.csv) District1 (aq_final_data_district1_2022_2023_input_final) District4 (aq_final_data_district4_2022_2023_input_final) Madrid City Pollution Protocol Pollution Protocol (PollutionProtocolSpanish.pdf) Madrid Pollution Ontology (Neo4J) Docker-compose (neo4j-docker-compose.yml) Pollution protocol (aq_level.owl) Pollution Ontology image (pollution_ontology.png) Import Ontology (PollutionOntologyToNeo4J) Export ontology results (PollutionOntologyToKafka) Statistical-based feature selection analysis Docker-compose (jupyter-docker-compose.yml) Feature selection Analysis (time-series-aq-2022.ipynb) LSTM-RNN tuning (aq_pass_lstm_tuning.ipynb)

Keywords

Traffic, Weather, Calendar, Air Quality

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
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