基于Lyapunov协同权重的信任度评价渐进控制模型

Trust Degree Evaluation Progressive Control Model Based on Collaborative Lyapunov Weight

由于网络用户数据呈现渐进性非线性特征分离,导致对网络用户的信任度评价控制不准,无法有效实现对用户的准确推荐。提出一种基于Lyapunov协同权重控制的电子商务用户信任度评价渐进控制模型,将未知扰动和语义建模误差转化为满足给定信任评价的约束矩阵,完成用户信任网络控制器设计,采用Lyapunov指数系统感知策略,对用户信任权重值进行自适应调整,构建用户推荐模型构建与网络信任度控制模型,设计用户信任权重值协同感知算法,基于Lyapunov协同权重的电子商务用户信任度评价渐进控制模型改进设计。实验结果表明,该算法实现电子商务用户信任度渐进控制,控制精度较高,地域的分布特性也更加均衡,真实反映电子商务用户信任度评价的动态性、自适应性和稳健性特征,展示了较好的应用性能。

Due to a network user data show progressive nonlinear characteristics of separation, resulting in trust evaluation for network user control are not allowed, unable to effectively realize accurate recommendation for users. An user trust de?gree evaluation progressive control model is proposed based on collaborative Lyapunov weight, the unknown disturbance and semantic modeling error transformation to meet the constraint matrix of the given trust evaluation, to complete the de?sign of user trust network controller, using Lyapunov index system perception strategy of users trust weights are adaptively adjusted to construct user recommendation model construction and network trust control model, design of user trust weights cooperative sensing algorithm, cooperative Lyapunov weight of user trust degree evaluation model based on improved de?sign of progressive control. The experimental results show that the algorithm of user trust degree incremental control, high control accuracy, distribution characteristics of regional has become more balanced, reflect the user trust degree evaluation of dynamic, adaptive and robust characteristics are obtained, it shows good application properties.