Yang et al., 2023 - Google Patents
HiGRN: a hierarchical graph recurrent network for global sea surface temperature predictionYang et al., 2023
View PDF- Document ID
- 17608454820563193971
- Author
- Yang H
- Li W
- Hou S
- Guan J
- Zhou S
- Publication year
- Publication venue
- ACM Transactions on Intelligent Systems and Technology
External Links
Snippet
Sea surface temperature (SST) is one critical parameter of global climate change, and accurate SST prediction is important to various applications, eg, weather forecasting, fishing directions, and disaster warnings. The global ocean system is unified and complex, and the …
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- G06N3/0472—Architectures, e.g. interconnection topology using probabilistic elements, e.g. p-rams, stochastic processors
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- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N99/00—Subject matter not provided for in other groups of this subclass
- G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
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- G06—COMPUTING; CALCULATING; COUNTING
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- G06N3/02—Computer systems based on biological models using neural network models
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- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
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- G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
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- G06—COMPUTING; CALCULATING; COUNTING
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- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
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- G06—COMPUTING; CALCULATING; COUNTING
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- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
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- G—PHYSICS
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