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ml_xco2's Introduction

The repository utilizes machine learning methods to construct spatially continuous CO2 distributions. Code and data are being uploaded one after another. If you have any questions, please email [email protected]. The relevant papers is "Mapping contiguous XCO2 by machine learning and analyzing the spatio-temporal variation in China from 2003 to 2019,https://doi.org/10.1016/j.scitotenv.2022.159588 " There is too much code data used in the project. Although I have disclosed some code and data, the corresponding code copyright is still owned by me. After all, this work took me a long time, if you want to refer to the code and data, please contact me. Thanks for your understanding. Maybe you can learn some tricks from messy code.

The code that has been opened is enough for some novice researchers to learn, and it is unlikely that I will open all the code, because that is a person's precious labor and knowledge. Open part of the code is already leading. We hope those who used this code could understand this.

ml_xco2's People

Contributors

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Stargazers

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Watchers

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ml_xco2's Issues

关于输入数据和输出数据的构建,以及测试集的选择。

这里是创建了一个0.25*0.25度的渔网(有N个网格),然后在每个格网里面计算XCO2的平均值作为模型的输出(标签)、计算环境变量的平均值作为输入的吗?每个月有N个值输入和输出值,那么十几年的值按照时间序列排序进行模型训练的吗?测试集的选择我可以理解成某些格网不参与训练,用作模型的验证吗? 希望得到您的回答,非常感谢🙏

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