Three gorges reservoir water temperature prediction method based on principal component analysis and neural network

Abstract

The invention discloses a three gorges reservoir water temperature prediction method based on principal component analysis and a neural network. The method comprises the steps of collecting a multivariable three gorges reservoir water temperature data set; judging the integrity of the three gorges reservoir water temperature data set; performing feature selection on the water temperature data; performing feature extraction, performing feature dimension reduction processing on the new data set by using a principal component analysis method, and dividing the data set subjected to feature dimension reduction processing into a training set and a test set; establishing a neural network prediction model, carrying out parameter optimization, inputting a training set, and carrying out sample learning; inputting a test set, and carrying out model evaluation; and measuring water temperature and characteristic data of the three gorges reservoir, carrying out characteristic selection and characteristic extraction, taking the characteristic selection and characteristic extraction as input of a neural network prediction model, and predicting the water temperature of the three gorges reservoir byadopting the neural network prediction model. According to the method, the prediction precision is effectively improved, the calculation amount of the prediction model is reduced, and the data rationality is improved.

Description

technical field [0001] The invention belongs to the field of hydrological monitoring of hydropower projects, and in particular relates to a water temperature prediction method of the Three Gorges Reservoir based on principal component analysis and neural network. Background technique [0002] Water temperature has both economic and ecological significance when considering issues such as river water quality and biological conditions. Water temperature is one of the river ecological parameters that determine the overall health of aquatic ecosystems, and has an extremely important impact on aquatic organisms and even aquatic ecosystems. Therefore, it is particularly important to effectively and accurately predict the water temperature. [0003] At present, there are few research methods for predicting water temperature in the Three Gorges Reservoir area. In the prior art, traditional empirical methods or numerical predictions based on mathematical models are mainly used, for ...

AI Technical Summary

Problems solved by technology

[0004] The technical problem of the present invention is that the water temperature prediction method in the Three Gorges Reservoir area of ​​the prior art has a large amount of data and redundant data, resulting in long model running time, poor prediction effect, and low prediction accuracy

Images