感知信任模式下移动社交电商盈利预测偏差分析算法

Algorithm for Predictive Deviation Analysis of Mobile SocialE-commerce Profit under Perceptual Trust Model

目的为了提高移动社交电商盈利预测偏差的自适应分析能力,提出感知信任模式下移动社交电商盈利预测偏差分析算法。方法提取移动社交电商盈利的关联规则特征量,采用模糊聚类方法对感知信任模式下移动社交电商盈利大数据进行自动聚类处理,构建移动社交电商盈利的统计序列分布模型;结合自适应寻优算法进行移动社交电商盈利预测,在感知信任模式下分析移动社交电商盈利预测偏差,并进行自适应调整,实现移动社交电商盈利预测偏差分析优化。结果仿真结果表明,采用该方法进行移动社交电商盈利预测的准确度较高,自适应分析能力得到保证。结论提高了移动社交电商盈利预测的自适应性和收敛性,可以将其应用到现实移动社交电商盈利预测中。

Objective To improve the self-adaptive analytic ability of profit forecast bias of mobile social E-commerce,this paper proposes a profit forecast bias analysis algorithm of mobile social E-commerce under the mode of perceived trust.Methods After extraction of the characteristics of association rules of mobile social E-commerce’s profit,fuzzy clustering method is used to automatically cluster the big data of mobile social E-commerce’s profit under the mode of perceived trust,and construct the statistical sequence distribution model of mobile social E-commerce’s profit;in combination with adaptive optimization algorithm,this paper forecasts the profit of mobile social E-commerce,and analyzes the profit forecast of mobile social E-commerce.Under the mode of perceived trust,the deviation and adaptive adjustment are performed to realize the analysis and optimization of profit forecast deviation of mobile social E-commerce.Results The simulation results show that the method has high accuracy in the profit forecast of mobile social E-commerce,and the adaptive analytic ability is guaranteed.Conclusion This algorithm improves the adaptability and convergence of mobile social E-commerce profit forecast,and can be applied to the real mobile social E-commerce profit forecast.