相关实验视频
基于生成对抗网络的电子商务产品价格预测模型的设计,具有自适应权重调整
Abuduaini Abudureheman1, Yan Zhao2, Aishanjiang Nilupaer3
1School of Economics, Guangdong University of Finance and Economics, GuangZhou, 510320, Guangdong, China. 18372075571@163.com.
Scientific reports
|July 11, 2025
概括
本研究介绍了适应性权重调整条件瓦斯斯坦生成对抗网络 (AWA-CWGAN),用于准确的电子商务价格预测. 这种新的算法有效地处理数据不平衡,与现有方法相比,实现了优越的预测性能.
科学领域:
- 人工智能的人工智能
- 机器学习 机器学习
- 数据科学数据科学数据科学
背景情况:
- 电子商务平台产生大量的交易数据,对于价格预测至关重要.
- 数据不平衡,过度装配和不足装配是预测各种商品价格的重大挑战.
研究的目的:
- 为准确的电子商务产品价格预测开发一个先进的生成对抗性网络模型.
- 解决数据不平衡,提高价格预测模型中的样本质量.
主要方法:
- 将条件生成对抗网络 (CGAN) 和瓦斯斯坦生成对抗网络 (WGAN) 集成到CWGAN模型中.
- 引入瓦瑟斯坦散射和删除利普希茨约束来缓解数据不平衡.
- 纳入适应性体重调整 (AWA) 和AWA-CWGAN算法的差异演变,其中包括社区学习和动态体重调整以适应遗传多样性.
主要成果:
- AWA-CWGAN算法实现了比标准算法更快的完全融合 (16-25%的全球进化代).
- 与基线方法相比,表现出优越的性能,准确率为88.8%,精度为88.81%,回忆率为89.255%,F1得分为87.95%.
结论:
- 拟议的AWA-CWGAN算法显著提高了电子商务产品价格预测的准确性.
- 该方法通过提高预测可靠性,为商家提供强大的决策支持.
相关概念视频
01:03Prediction Intervals
2.3K
The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
2.3K
01:52Regression Toward the Mean
6.5K
Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when...
6.5K
02:52Predicting 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
02:27Predicting 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
00:57Weighted Mean
5.3K
While taking the arithmetic, geometric, or harmonic mean of a sample data set, equal importance is assigned to all the data points. However, all the values may not always be equally important in some data sets. An intrinsic bias might make it more important to give more weightage to specific values over others.
For example, consider the number of goals scored in the matches of a tournament. While computing the average number of goals scored in the tournament, it may be more important to...
For example, consider the number of goals scored in the matches of a tournament. While computing the average number of goals scored in the tournament, it may be more important to...
5.3K
01:11Regression Analysis
6.1K
Regression analysis is a statistical tool that describes a mathematical relationship between a dependent variable and one or more independent variables.
In regression analysis, a regression equation is determined based on the line of best fit– a line that best fits the data points plotted in a graph. This line is also called the regression line. The algebraic equation for the regression line is called the regression equation. It is represented as:
In regression analysis, a regression equation is determined based on the line of best fit– a line that best fits the data points plotted in a graph. This line is also called the regression line. The algebraic equation for the regression line is called the regression equation. It is represented as:
6.1K