深度可分离卷积与DSCNCF模型以及数字经济的优化机制,用于在销售订单推算法下的智能制造
1Guangdong University of Science and Technology, Dongguan, 523000, China. qiujin@gdust.edu.cn.
Scientific reports
|August 15, 2025
概括
深度学习优化了智能制造中的销售订单管理,提高了效率和客户满意度. 深度可分离的卷积神经协作过 (DSC-NCF) 算法在关键性能指标中显著超过基准.
科学领域:
- 智能制造 智能制造是一种智能制造.
- 数字经济数字经济
- 人工智能的人工智能
- 运营管理 运营管理
背景情况:
- 智能制造企业在数字经济中优化销售订单管理方面面临挑战.
- 智能转型需要先进的解决方案来提高效率和客户满意度.
- 深度学习为增强复杂的操作流程提供了潜力.
研究的目的:
- 探索深度学习在智能制造的销售订单管理中的优化作用.
- 研究深度学习推动工业结构升级和智能转型的机制.
- 评估与传统方法对比的新型深度学习算法的性能.
主要方法:
- 开发基于深度学习的智能推平台,使用深度可分离卷积神经协作过 (DSC-NCF) 算法.
- 利用阿里巴巴的点击和转换预测 (Ali-CCP) 智能制造数据集.
- 与传统的神经协作过 (NCF) 和因子化机器 (FM) 算法进行比较分析.
主要成果:
- 与NCF和FM相比,DSC-NCF算法在所有评估指标 (准确性,回忆,F1得分,AUC) 中表现优异.
- 在100个训练时代中,DSC-NCF实现了0.91的精度,0.92的回忆,0.94的F1得分和0.99.99的AUC.
- 对于DSC-NCF,在特征提取和模型优化方面观察到显著的优势,使得用户-项目关系能够更好地捕获.
结论:
- 深度学习,特别是DSC-NCF算法,为优化智能制造中的销售订单管理提供了有效的解决方案.
- 改进的订单管理可以提高客户满意度,并促进工业结构升级和智能转型.
- 该研究为制造企业在数字经济中利用人工智能提供理论支持和技术途径.
相关概念视频
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving
101
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...
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
101
Predicting Products: Substitution vs. Elimination
12.3K
When a nucleophile and an alkyl halide react, nucleophilic substitution and β-elimination reactions compete to generate products.
The following factors can influence the mechanisms competing against each other:
The following factors can influence the mechanisms competing against each other:
12.3K
Predicting Products: SN1 vs. SN2
14.0K
Nucleophilic substitution reactions of alkyl halides can proceed via an SN1 or an SN2 mechanism. While in SN2 reactions, the nucleophile attacks the substrate simultaneously as the leaving group departs, in SN1 reactions, the substrate first dissociates to give the carbocation intermediate. Various factors such as the structure of the substrate, the strength of the nucleophile, and the nature of the solvent promote one mechanism over the other.
With increased substitution on the alkyl halide,...
With increased substitution on the alkyl halide,...
14.0K
Factorial Design
13.3K
Factorial Analysis is an experimental design that applies Analysis of Variance (ANOVA) statistical procedures to examine a change in a dependent variable due to more than one independent variable, also known as factors. Changes in worker productivity can be reasoned, for example, to be influenced by salary and other conditions, such as skill level. One way to test this hypothesis is by categorizing salary into three levels (low, moderate, and high) and skills sets into two levels (entry level...
13.3K
Response Surface Methodology
266
Response Surface Methodology (RSM) is a collection of statistical and mathematical techniques used to develop, improve, and optimize processes. It is particularly valuable when many input variables or factors potentially influence a response variable.
The process of RSM involves several key steps:
The process of RSM involves several key steps:
266


