Air Pollutant Concentration Forecasting with WTMP: Wavelet Transform-Based Multilayer Perceptron
Atmospheric pollutants’ real-time changes and the internal interactions among various data make it challenging to efficiently predict concentration variations. In order to extract more information from the time series of pollutants and improve the accuracy of prediction models, we propose a type of...
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| Format: | Article |
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MDPI AG
2024-10-01
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| Series: | Atmosphere |
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| Online Access: | https://www.mdpi.com/2073-4433/15/11/1296 |
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| author | Xiaoling Wang Liangzhao Tao Mingliang Fu Qi Wang |
| author_facet | Xiaoling Wang Liangzhao Tao Mingliang Fu Qi Wang |
| author_sort | Xiaoling Wang |
| collection | DOAJ |
| description | Atmospheric pollutants’ real-time changes and the internal interactions among various data make it challenging to efficiently predict concentration variations. In order to extract more information from the time series of pollutants and improve the accuracy of prediction models, we propose a type of Multilayer Perceptron model based on wavelet decomposition, named Wavelet Transform-based Multilayer Perceptron (WTMP) model. This model decomposes pollutant data through overlapping discrete wavelet transforms to extract non-stationarity and nonlinear dependencies in the time series. It combines the decomposed data with static covariate information such as data collection time and inputs them into an improved Multilayer Perceptron (MLP) model, reconstructing and outputting the prediction results. Finally, the model is validated using atmospheric pollutant data collected at a specific location in Ruian City, Zhejiang Province, China. The results indicate that the model performs well with minimal prediction errors. |
| format | Article |
| id | doaj-art-089f95cf5e3c47cc9662fe655dd74ca2 |
| institution | OA Journals |
| issn | 2073-4433 |
| language | English |
| publishDate | 2024-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Atmosphere |
| spelling | doaj-art-089f95cf5e3c47cc9662fe655dd74ca22025-08-20T01:53:52ZengMDPI AGAtmosphere2073-44332024-10-011511129610.3390/atmos15111296Air Pollutant Concentration Forecasting with WTMP: Wavelet Transform-Based Multilayer PerceptronXiaoling Wang0Liangzhao Tao1Mingliang Fu2Qi Wang3School of Information and Electronic Engineering, Zhejiang Gongshang University, Hangzhou 310018, ChinaSchool of Information and Electronic Engineering, Zhejiang Gongshang University, Hangzhou 310018, ChinaState Environmental Protection Key Laboratory of Vehicle Emission Control and Simulation, Chinese Research Academy of Environmental Sciences, Beijing 100012, ChinaCollege of Life and Environmental Sciences, Wenzhou University, Wenzhou 325000, ChinaAtmospheric pollutants’ real-time changes and the internal interactions among various data make it challenging to efficiently predict concentration variations. In order to extract more information from the time series of pollutants and improve the accuracy of prediction models, we propose a type of Multilayer Perceptron model based on wavelet decomposition, named Wavelet Transform-based Multilayer Perceptron (WTMP) model. This model decomposes pollutant data through overlapping discrete wavelet transforms to extract non-stationarity and nonlinear dependencies in the time series. It combines the decomposed data with static covariate information such as data collection time and inputs them into an improved Multilayer Perceptron (MLP) model, reconstructing and outputting the prediction results. Finally, the model is validated using atmospheric pollutant data collected at a specific location in Ruian City, Zhejiang Province, China. The results indicate that the model performs well with minimal prediction errors.https://www.mdpi.com/2073-4433/15/11/1296atmospheric pollutantswavelet decompositionmulti-layer perceptron model |
| spellingShingle | Xiaoling Wang Liangzhao Tao Mingliang Fu Qi Wang Air Pollutant Concentration Forecasting with WTMP: Wavelet Transform-Based Multilayer Perceptron Atmosphere atmospheric pollutants wavelet decomposition multi-layer perceptron model |
| title | Air Pollutant Concentration Forecasting with WTMP: Wavelet Transform-Based Multilayer Perceptron |
| title_full | Air Pollutant Concentration Forecasting with WTMP: Wavelet Transform-Based Multilayer Perceptron |
| title_fullStr | Air Pollutant Concentration Forecasting with WTMP: Wavelet Transform-Based Multilayer Perceptron |
| title_full_unstemmed | Air Pollutant Concentration Forecasting with WTMP: Wavelet Transform-Based Multilayer Perceptron |
| title_short | Air Pollutant Concentration Forecasting with WTMP: Wavelet Transform-Based Multilayer Perceptron |
| title_sort | air pollutant concentration forecasting with wtmp wavelet transform based multilayer perceptron |
| topic | atmospheric pollutants wavelet decomposition multi-layer perceptron model |
| url | https://www.mdpi.com/2073-4433/15/11/1296 |
| work_keys_str_mv | AT xiaolingwang airpollutantconcentrationforecastingwithwtmpwavelettransformbasedmultilayerperceptron AT liangzhaotao airpollutantconcentrationforecastingwithwtmpwavelettransformbasedmultilayerperceptron AT mingliangfu airpollutantconcentrationforecastingwithwtmpwavelettransformbasedmultilayerperceptron AT qiwang airpollutantconcentrationforecastingwithwtmpwavelettransformbasedmultilayerperceptron |