Methods used for handling and quantifying model uncertainty of artificial neural network models for air pollution forecasting
SM Cabaneros, B Hughes - Environmental Modelling & Software, 2022 - Elsevier
The use of data-driven techniques such as artificial neural network (ANN) models for
outdoor air pollution forecasting has been popular in the past two decades. However …
outdoor air pollution forecasting has been popular in the past two decades. However …
Calibration protocol for paramics microscopic traffic simulation model: application of neuro-fuzzy approach
This study investigated the challenges of calibration of the PARAMICS microscopic
simulation model for the local traffic conditions in the Kingdom of Saudi Arabia. It proposed …
simulation model for the local traffic conditions in the Kingdom of Saudi Arabia. It proposed …
Development of ANFIS models for PM short-term prediction. case study
SF Mihalache, M Popescu - 2016 8th International Conference …, 2016 - ieeexplore.ieee.org
The growing rate of urban and industrial development leads to high levels of air pollution in
most countries around the world. Because air pollution has a major impact on human health …
most countries around the world. Because air pollution has a major impact on human health …
Nonlinear partial least squares for consistency analysis of meteorological data
Z Meng, S Zhang, Y Yang, M Liu - Mathematical Problems in …, 2015 - Wiley Online Library
Considering the different types of error and the nonlinearity of the meteorological
measurement, this paper proposes a nonlinear partial least squares method for consistency …
measurement, this paper proposes a nonlinear partial least squares method for consistency …