化学测量中的Etemadi回归:基于可靠性的建模和预测程序.
Sepideh Etemadi1, Mehdi Khashei1
1Department of Industrial and Systems Engineering, Isfahan University of Technology (IUT), Isfahan, 84156-83111, Iran.
Heliyon
|March 4, 2024
概括
这项研究引入了一种新的基于可靠性的化学测量建模策略,在78.95%的病例中表现优于传统的基于精度的模型. 可靠性显著提高了化学分析中的模型通用性和预测稳定性.
科学领域:
- 化学测量 化学测量 化学测量
- 化学分析 化学分析
- 过程优化 过程优化
背景情况:
- 化学分析中的预测模型需要高度的概括性,这是当前化学测量学的挑战.
- 现有的模型主要使用基于准确性的策略,尽量减少训练数据错误.
- 基于可靠性的方法,如Etemadi方法,显示出希望,但在化学测量中未得到充分利用.
研究的目的:
- 通过将可靠性纳入预测程序来弥补化学度模型中的差距.
- 提出一种基于风险的新型建模策略,以提高模型的通用性和稳定性.
- 量化可靠性与准确性对概括性和不确定性建模的影响.
主要方法:
- 使用基于最佳可靠性的参数估计过程开发一般设计结构.
- 引入基于风险的建模策略,以尽量减少不同实验条件下的性能变化.
- 在各种领域进行实证评估,包括药理学,生物化学和地球化学.
主要成果:
- 基于可靠性的模型在78.95%的评估案例中表现出比基于准确性的模型更好的性能.
- 在平均绝对误差 (MAE),平均平方误差 (MSE) 和根平均平方误差 (RMSE) 中观察到显著改善.
- 统计分析证实,与准确性相比,可靠性对概括性的影响更大.
结论:
- 基于可靠性的建模为化学测量的传统基于精度的方法提供了强大的替代方案.
- 拟议的战略增强了化学实验室实验的预测稳定性和通用性.
- 整合可靠性对于推进化学度模型性能和不确定性量化至关重要.
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