Standout Papers

A machine learning calibration model using random forests to improve sensor performance for lower-cost a... 2018 2026 2020 2023 348
  1. A machine learning calibration model using random forests to improve sensor performance for lower-cost air quality monitoring (2018)
    Naomi Zimmerman, Albert A. Presto et al. Atmospheric measurement techniques

Immediate Impact

30 standout
Sub-graph 1 of 15

Citing Papers

Assessing the effectiveness of long short-term memory and artificial neural network in predicting daily ozone concentrations in Liaocheng City
2025 Standout
Integrating Artificial Intelligence Agents with the Internet of Things for Enhanced Environmental Monitoring: Applications in Water Quality and Climate Data
2025 Standout
3 intermediate papers

Works of Aliaksei Hauryliuk being referenced

Development of a general calibration model and long-term performance evaluation of low-cost sensors for air pollutant gas monitoring
2019
A machine learning calibration model using random forests to improve sensor performance for lower-cost air quality monitoring
2018 Standout

Author Peers

Author Last Decade Papers Cites
Aliaksei Hauryliuk 661 763 286 12 868
Franck René Dauge 650 800 254 6 899
Carl Malings 703 747 322 27 1.0k
Andreas N. Skouloudis 518 532 225 23 878
Anthony Butterfield 616 650 256 19 928
Emily Snyder 484 492 172 18 833
P. Goyal 626 545 284 28 935
Ricardo Piedrahita 471 406 205 28 916
Anssi Järvinen 543 322 384 26 871
Andrea L. Clements 721 469 556 20 933
Said Munir 635 509 320 45 870

All Works

Loading papers...

Rankless by CCL
2026