Marine fishery resource dynamic prediction based on CNN-XGBoost fusion model - News Summed Up

Marine fishery resource dynamic prediction based on CNN-XGBoost fusion model


The marine fishery resource datasets used in this study were obtained from multiple sources, with access information provided below to facilitate reproducibility and follow-up research. Access requires registration (free for research purposes) and adherence to the CMA data policy (http://data.cma.cn/en/site/index.html). Station-level daily observations can be requested through the portal’s data ordering system, with typical processing time of 3-5 business days for historical data requests. Ocean current velocity data were obtained from the China High-Frequency Radar Ocean Observation Network operated by the State Oceanic Administration, available through collaborative research agreements. The Python code implementing the CNN-XGBoost fusion model, including data preprocessing scripts, model architecture definitions, training procedures, and evaluation metrics, will be made publicly available on GitHub (https://github.com/[username]/CNN-XGBoost-Marine-Fishery) upon publication acceptance, licensed under MIT License to facilitate reproducibility and encourage further methodological development by the research community.


Source: CNN December 21, 2025 19:10 UTC



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