基于多目标优化和遗传算法的会计系统实时任务参数选择方法
Rongjie Qin1,2, Muhammad Shahbaz3
1Wuhan Technology and Business University, Wuhan, China.
PeerJ. Computer science
|April 25, 2024
概括
本研究介绍了一种使用多式联运信息嵌入的先进会计系统,以及用于参数选择的并行遗传算法. 这种新的方法通过显著的绩效指标增强了企业的财务状况.
科学领域:
- 计算机科学 计算机科学
- 人工智能的人工智能
- 会计信息系统 会计信息系统
背景情况:
- 数字经济需要企业会计系统的进步.
- 现有的会计系统需要加快更新和发展以满足新的需求.
研究的目的:
- 为优化会计系统提出一种新的参数选择方法.
- 增强会计模型的特征提取和信息传感能力.
主要方法:
- 使用多式联运信息嵌入与双分支结构和特征金字塔网络的会计特征提取.
- 通过平行遗传算法进行多目标参数选择,集成到双分支模型培训中.
- 开发使用循环变压器的会计系统评估方法.
主要成果:
- 提出的方法实现了高F值的87.6%,mAP的83.5%,准确度的83.4%.
- 实验结果显示,模型感知会计信息的能力显著提高.
- 该方法位于一个先进的全球水平,用于增强会计系统.
结论:
- 多式联运嵌入和遗传算法优化的综合方法有效地增强了会计系统.
- 循环的基于变压器的评估方法显示了改善企业财务状况的巨大潜力.
- 这项研究为现代化数字经济中的会计实践提供了一个可扩展的解决方案.
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