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Building a model for choosing a strategy for reducing air pollution based on data predictive analysis
- Publication Year :
- 2022
- Publisher :
- Zenodo, 2022.
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Abstract
- This paper formalizes the model of choosing a strategy for reducing air pollution in an urban environment. The model involves determining the optimal location of biotechnological systems – biotechnological filter systems or smart air purification devices based on solving the problem of discrete optimization, taking into consideration the forecast of the air quality index. Two subtasks have been formalized, which make it possible to form a strategy for reducing air pollution. To solve one of the subtasks, a combined selective model for predicting the time series of the Air Quality Index (CSM) was built. The combined model software suite consists of the EMD-ESM hybrid model (Empirical Mode Decomposition-Exponential Smoothing Model), the HWM additive model (Holt-Winters Model), and the adaptive TLM (Trigg-Lich Model). To verify the proposed combined selective model, the time series of air quality indices (AQI) for the city of Nur-Sultan (data from 2010‒2021, period 6 hours) were selected. As a result of verification, it was established that in the case of short-term forecasting of the air quality index time series, the EMD-ESM model has an advantage according to the criterion of a minimum root mean square error (RMSE), δ=0.11. For the case of medium-term forecasting of 3
- Subjects :
- EDM
Applied Mathematics
Mechanical Engineering
air pollution
selection problem
Energy Engineering and Power Technology
combined selective forecasting model
Industrial and Manufacturing Engineering
Computer Science Applications
Control and Systems Engineering
AQI
Management of Technology and Innovation
Environmental Chemistry
Electrical and Electronic Engineering
ESP
Food Science
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Accession number :
- edsair.doi.dedup.....2196957157d088bd24be84c733039c8e