Ling Jin
Publications
Viewing 25 of 41 publications
2024
Macroscopic Traffic Modeling Using Probe Vehicle Data: A Machine Learning Approach." Data Science for Transportation 6.3 (2024).
, , , , , , , , , and . "Technology progress and clean vehicle policies on fleet turnover and equity: insights from household vehicle fleet micro-simulations with ATLAS." Transportation Planning and Technology (2024) 1–24.
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2023
Leveraging Probe Data and Machine Learning to Derive and Interpret Macroscopic Fundamental Diagrams Across U.S. Cities." 2023 IEEE International Conference on Big Data (BigData). Sorrento, Italy: IEEE, 2023.
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Location-Specific Control of Precursor Emissions to Mitigate Photochemical Air Pollution." Environmental Science & Technology 57.26 (2023) 9693–9701.
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What Makes You Hold on to That Old Car? Joint Insights from Machine Learning and Multinomial Logit on Vehicle-level Transaction Decisions." Frontiers in Future Transportation - Connected Mobility and Automation (2022).
, , , , , , , , , , , and . "Responses of Photochemical Air Pollution in California’s San Joaquin Valley to Spatially and Temporally Resolved Changes in Precursor Emissions." Environmental Science & Technology 56.11 (2022) 7074–7082.
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Performance of the Gold Standard and Machine Learning in Predicting Vehicle Transactions." 2021 IEEE International Conference on Big Data (Big Data). Orlando, FL, USA: IEEE, 2021.
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, , , , , , and . "Correlation networks of air particulate matter (PM2.5): a comparative study." Applied Network Science 6.1 (2021).
, , , and . "Strategies to reduce PM2.5 and O3 together during late summer and early fall in San Joaquin Valley, California." Atmospheric Research (2021) 105633.
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Smelly-Odor Webtool (Smelly) v1." 2020.
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Life-Cycle Greenhouse Gas Emissions and Human Health Trade-Offs of Organic Waste Management StrategiesLife-Cycle Greenhouse Gas Emissions and Human Health Trade-Offs of Organic Waste Management Strategies." Environmental Science & Technology 54.15 (2020) 9200–9209.
, , , , , , , , , , and . "Winners are not keepers: Characterizing household engagement, gains, and energy patterns in demand response using machine learning in the United States." Energy Research & Social Science 70 (2020).
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Machine Learning for Prediction of Mid to Long Term Habitual Transportation Mode Use." 2019 IEEE International Conference on Big Data (Big Data)2019 IEEE International Conference on Big Data (Big Data). Los Angeles, CA, USA: IEEE, 2019.
, , , , , and . "Spillover as a cause of bias in baseline evaluation methods for demand response programs." Applied Energy 250 (2019) 344–357.
, , , and . "Evaluating the Effects of Missing Values and Mixed Data Types on Social Sequence Clustering Using t-SNE Visualization." Journal of Data and Information Quality 11.2 (2019) 1–22.
, , , , , and . "Describing the users: Understanding adoption of and interest in shared, electrified, and automated transportation in the San Francisco Bay Area." Transportation Research Part D: Transport and Environment 71 (2019) 283–301.
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Accelerating the Deployment of Anaerobic Digestion to Meet Zero Waste Goals." Environmental Science & Technology 52.23 (2018) 13663–13669.
, , , , , , , and . "Temporal and geographic drivers of biomass residues in California." Resources, Conservation and Recycling 139 (2018) 287–297.
, , , , and . "Dynamic Geospatial Modeling of the Building Stock To Project Urban Energy Demand." Environmental Science & Technology 52.14 (2018) 7604–7613.
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