A data-driven approach to the forecasting of ground-level ozone concentration

  title={A data-driven approach to the forecasting of ground-level ozone concentration},
  author={Dario Marvin and Lorenzo Nespoli and Davide Strepparava and Vasco Medici},
2 Citations



A real-time hourly

  • 2019

Calculated influence of temperature

  • 1995

A Unified Approach to Interpreting Model Predictions

A unified framework for interpreting predictions, SHAP (SHapley Additive exPlanations), which unifies six existing methods and presents new methods that show improved computational performance and/or better consistency with human intuition than previous approaches.

High-Resolution PV Forecasting from Imperfect Data: A Graph-Based Solution

Operating power systems with large amounts of renewables requires predicting future photovoltaic (PV) production with fine temporal and spatial resolution. State-of-the-art techniques combine

From local explanations to global understanding with explainable AI for trees

An explanation method for trees is presented that enables the computation of optimal local explanations for individual predictions, and the authors demonstrate their method on three medical datasets.

NGBoost: Natural Gradient Boosting for Probabilistic Prediction

NGBoost generalizes gradient boosting to probabilistic regression by treating the parameters of the conditional distribution as targets for a multiparameter boosting algorithm, and shows how the Natural Gradient is required to correct the training dynamics of the authors' multiparameters boosting approach.

Meteorology and Climate Influences on Tropospheric Ozone: a Review of Natural Sources, Chemistry, and Transport Patterns

Tropospheric ozone is a key air pollutant and greenhouse gas. Its fate strongly depends on meteorological conditions and therefore subject to climate change influences. Such dependences through

Calculated Influence of Temperature-Related Factors on Ozone Formation Rates in the Lower Troposphere

Abstract Using an atmospheric chemical reaction mechanism applied to air parcels near the earth's surface, the sensitivities ozone (O3) formation rates are quantified for changes in four

Spatio-temporal violent event prediction using Gaussian process regression

This work analyzes the predictive ability of data-derived Gaussian process models compared to a generalized linear model and develops a computationally intensiveGaussian process modeling approach that exploits the size and complexity of the violent conflict dataset to identify appropriate basis vectors for the model.

On the background photochemistry of tropospheric ozone

We present a largely tutorial overview of the main processes that influence the photochemistry of the background troposphere. This is mostly driven by the photolysis of ozone by solar ultraviolet