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相关概念视频

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

52
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
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Decision Making: P-value Method01:09

Decision Making: P-value Method

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The process of hypothesis testing based on the P-value method includes calculating the P- value using the sample data and interpreting it.
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim  is also stated. These statements can act as null and alternative hypotheses:  a null hypothesis would be a neutral statement while the alternative hypothesis can...
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Decision Making: Traditional Method01:14

Decision Making: Traditional Method

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The process of hypothesis testing based on the traditional method includes calculating the critical value, testing the value of the test statistic using the sample data, and interpreting these values.
First, a specific claim about the population parameter is decided based on the research question and is stated in a simple form. Further, an opposing statement to this claim is also stated. These statements can act as null and alternative hypotheses, out of which a null hypothesis would be a...
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Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

106
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence...
106
Pharmacokinetic Models: Comparison and Selection Criterion01:26

Pharmacokinetic Models: Comparison and Selection Criterion

69
Physiological and compartmental models are valuable tools used in studying biological systems. These models rely on differential equations to maintain mass balance within the system, ensuring an accurate representation of the dynamic processes at play.
Physiological models take a detailed approach by considering specific molecular processes. They can predict drug distribution, metabolism, and elimination changes, providing a comprehensive understanding of how drugs interact with the body.
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Actuarial Approach01:20

Actuarial Approach

77
The actuarial approach, a statistical method originally developed for life insurance risk assessment, is widely used to calculate survival rates in clinical and population studies. This method accounts for participants lost to follow-up or those who die from causes unrelated to the study, ensuring a more accurate representation of survival probabilities.
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
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相关实验视频

Updated: Jun 27, 2025

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
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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
PubMed
概括
此摘要是机器生成的。

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.

关键词:
会计系统会计系统会计系统数字经济数字经济遗传算法 遗传算法 遗传算法多目标优化多目标优化参数选择参数选择

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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.