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利用最先进的技术:在化学和材料科学领域的机器学习项目
Yuheng Li1,2,3,4, Fengming Guo1,2,3,4, Shui-Yang Lien5
1College of Chemistry and Materials Science, Fujian Normal University, Fuzhou, Fujian 350108, China.
Physical chemistry chemical physics : PCCP
|April 9, 2025
概括
机器学习 (ML) 在材料科学和化学方面提供了机会,但有可能产生偏见的结果. 本综述指导研究人员使用标准化的ML来获得可靠的科学结果.
科学领域:
- 材料科学 材料科学 材料科学
- 化学 化学 化学
- 计算科学 计算科学
背景情况:
- 机器学习 (ML) 正在改变科学研究方法.
- 错误的ML应用可能会导致偏见和误导性的研究结果.
研究的目的:
- 审查材料科学和化学中的ML应用.
- 在整个ML过程中分析潜在的问题和风险.
- 为科学合理和符合ML使用提供指导.
主要方法:
- 在材料科学和化学中审查ML应用过程.
- 在每个阶段 (数据管理,模型构建,评估,数据报告) 深入分析潜在问题.
- 案例研究说明了风险和挑战.
主要成果:
- 在跨研究阶段的ML实施中确定了风险和挑战.
- 强调需要标准化的ML实践.
- 总结了确保研究可靠性和有效性的策略.
结论:
- 标准化的ML使用对于材料科学和化学的科学完整性至关重要.
- 研究人员需要实际指导,以避免陷,并促进严格的做法.
- 解决ML应用中的当前危机对于推动这些领域的发展至关重要.
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