使用模糊逻辑和数学模型来预测工业企业的财务效率
1Physical Education College, Henan Sport University, Zhengzhou, Henan, China.
PloS one
|October 30, 2025
概括
本研究介绍了用于准确预测工业金融效率的FuzzyMath方法. 它克服了传统方法的局限性,在检测财务绩效方面达到99.23%的准确性.
科学领域:
- 工业工程 工业工程 工业工程
- 财务管理 财务管理
- 计算智能是一种计算智能.
背景情况:
- 工业企业由于其动态性质,需要有效的财务效率检测.
- 传统的统计和机器学习方法与高维数据,不确定性和稳定性作斗争.
- 现有的预测模型在复杂的工业环境中面临着可扩展性问题.
研究的目的:
- 为工业应用开发有效的财务效率检测流程.
- 解决传统预测方法的不确定性,稳定性和可扩展性问题.
- 为了提高预测准确度,使用集成的模糊逻辑和数学模型.
主要方法:
- 混逻辑和数学模型的整合,称为FuzzyMath方法.
- 用多变量和salp优化算法利用模糊系统.
- 优化会员功能,模糊的规则和模糊化过程.
主要成果:
- zzyMath方法有效地预测了高识别准确度的财务业绩.
- 集成的优化算法提高了整体系统效率.
- 优化的模糊组件将计算困难降到最低,并处理不确定性.
结论:
- zzyMath方法在预测工业财务效率方面保证了99.23%的准确性.
- 这种方法有效地管理不确定性,并提高财务业绩预测的稳定性.
- zzyMath方法为工业金融分析提供了一个可扩展和准确的解决方案.
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