Prediction of the Hydrogen Leak Concentration based on Improved PSO-BP Neural Network

Yang, Lai; Xia, Feng; Ji, Xiang

doi:10.1109/iciba50161.2020.9276829

Cited by 1 publication

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References 5 publications

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“…Temperature changes will not only affect the global climate and ecosystem, but also have a profound impact on people's social practice. Therefore, temperature prediction is a challenging and significant work [1]. Temperature prediction has been studied by many scholars, such as decision tree, statistics, vector regression and neural network.…”

Section: Introductionmentioning

confidence: 99%

A Hybrid CNN-LSTM model for temperature forecasting

Guo¹

2023

International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2023)

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Temperature prediction has always been a difficult point in meteorological prediction. It not only affects the global climate and ecosystem, but also has a profound impact on people 's social practice. In recent years, the temperature prediction mostly adopts the method of constructing neural network, because the method of decision tree, statistics and vector regression ignores the time series dependence, but the neural network-based models have limited its accuracy. Many scholars like to use CNN or LSTM model alone, and both of them are still lacking. Therefore, this paper proposes to combine CNN and LSTM models, which can not only give full play to the advantages of CNN model in processing data quickly, but also use the memory function of LSTM model to process temperature data with strong time series. The experimental results show that the CNN-LSTM model is more accurate than the CNN and LSTM models alone in predicting temperature.

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Section: Introductionmentioning

confidence: 99%

A Hybrid CNN-LSTM model for temperature forecasting

Guo¹

2023

International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2023)

View full text Add to dashboard Cite

show abstract

Prediction of the Hydrogen Leak Concentration based on Improved PSO-BP Neural Network

Cited by 1 publication

References 5 publications

A Hybrid CNN-LSTM model for temperature forecasting

A Hybrid CNN-LSTM model for temperature forecasting

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