A trained model for real-time pollution data prediction
By combining LSTM and MAML models, the MAML-LSTM model was designed to solve the problems of large sample requirements and RNN gradient in contaminated data prediction, achieving high accuracy and strong generalization in contaminated data prediction on small sample datasets.
CN116187389BActive Publication Date: 2026-06-16CHENGDU ZVAN TECH
Patent Information
- Application Number
- CN202310202365.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2023-03-06
- Publication Date
- 2026-06-16
- Estimated Expiration
- 2043-03-06
Smart Images
Figure CN116187389B_ABST
Abstract
The application relates to a training model for real-time pollution data prediction, which takes an LSTM as a basic model, accelerates the convergence speed of the LSTM through MAML, and reduces the limitation of the LSTM model data set. The application has the beneficial effects that the limitation of insufficient data volume of a pollution factor data set is broken through, and the balance between single factor prediction and multi-target prediction can be realized; the model can realize the function of accelerating the training of a prediction model while keeping the prediction accuracy unchanged; the model is light in volume, and the generalization of the training result on a small sample data set training is strong.
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Citation Information
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