Exploration and Prediction of Lake Water Levels Based on the MOACO Algorithm and CNN-LSTM Model
Author:
Affiliation:
1. University of Science and Technology Liaoning,School of Sciences,Anshan,China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10659854/10659821/10660054.pdf?arnumber=10660054
Reference5 articles.
1. Analyzing the impact of MOACO components: An algorithmic study on the multi-objective shortest path problem
2. A realistic variant of bi-objective unrelated parallel machine scheduling problem: NSGA-II and MOACO approaches
3. Incorporating multiple grid-based data in CNN-LSTM hybrid model for daily runoff prediction in the source region of the Yellow River Basin
4. Coupling a hybrid CNN-LSTM deep learning model with a Boundary Corrected Maximal Overlap Discrete Wavelet Transform for multiscale Lake water level forecasting
5. Axiomatic characterization of PageRank
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