Prediction of Benzene Concentration of Air in Urban Area Using Deep Neural Network

Ray, Radhika; Haldar, Siddhartha; Biswas, Subhadeep; Mukherjee, Ruptirtha; Banerjee, Shayan; Chatterjee, Sankhadeep

doi:10.1007/978-981-13-1544-2_38

Cited by 2 publications

(2 citation statements)

References 17 publications

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“…Deep learning is also widely used in air quality prediction due to its powerful nonlinear fitting ability. Ray et al proposed a prediction model based on deep learning [ 14 ]. It uses correlation analysis to find the most appropriate feature set, which is used to predict air quality.…”

Section: Introductionmentioning

confidence: 99%

An Empirical Mode Decomposition Fuzzy Forecast Model for Air Quality

Jiang

Zhu

Shen

et al. 2022

Entropy

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Air quality has a significant influence on people’s health. Severe air pollution can cause respiratory diseases, while good air quality is beneficial to physical and mental health. Therefore, the prediction of air quality is very important. Since the concentration data of air pollutants are time series, their time characteristics should be considered in their prediction. However, the traditional neural network for time series prediction is limited by its own structure, which makes it very easy for it to fall into a local optimum during the training process. The empirical mode decomposition fuzzy forecast model for air quality, which is based on the extreme learning machine, is proposed in this paper. Empirical mode decomposition can analyze the changing trend of air quality well and obtain the changing trend of air quality under different time scales. According to the changing trend under different time scales, the extreme learning machine is used for fast training, and the corresponding prediction value is obtained. The adaptive fuzzy inference system is used for fitting to obtain the final air quality prediction result. The experimental results show that our model improves the accuracy of both short-term and long-term prediction by about 30% compared to other models, which indicates the remarkable efficacy of our approach. The research of this paper can provide the government with accurate future air quality information, which can take corresponding control measures in a targeted manner.

show abstract

Section: Introductionmentioning

confidence: 99%

An Empirical Mode Decomposition Fuzzy Forecast Model for Air Quality

Jiang

Zhu

Shen

et al. 2022

Entropy

View full text Add to dashboard Cite

show abstract

“…Deep learning is also widely used in air quality prediction due to its powerful nonlinear fitting ability. Ray et al proposed a prediction model based on deep learning 12 . It uses correlation analysis to find the most appropriate feature set which is used to predict air quality.…”

Section: Introductionmentioning

confidence: 99%

An Empirical Mode Decomposition Fuzzy Forecast Model for Air Quality

Chen

Zhu

Sheng

et al. 2021

Preprint

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Air quality is related to people's health. Severe air pollution can cause respiratory diseases, while good air quality is beneficial to physical and mental health. Therefore, the prediction of air quality is very important. As an important algorithm for signal analysis, empirical mode decomposition can analyze the change trend of air quality well, smooth the complex and changeable air quality data, and get the change trend of air quality under different time scales. According to the change trend under different time scales, the extreme learning machine is used for training, and the corresponding prediction value is obtained. The adaptive fuzzy inference system is used for fitting to obtain the final air quality prediction result. The experimental results show that the signal decomposition fuzzy prediction model has a good learning ability and has good accuracy in predicting the concentration of various pollutants in air quality.

show abstract

Prediction of Benzene Concentration of Air in Urban Area Using Deep Neural Network

Cited by 2 publications

References 17 publications

An Empirical Mode Decomposition Fuzzy Forecast Model for Air Quality

An Empirical Mode Decomposition Fuzzy Forecast Model for Air Quality

An Empirical Mode Decomposition Fuzzy Forecast Model for Air Quality

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