基于粒子群优化的SVM的第三方物流企业客户满意度评价研究

Research on Customer Satisfaction Evaluation in 3PL Company Based on SVM Optimized by PSO

文中从第三方物流企业角度出发,以为客户提供标准化、专业化、个性化的服务,提高客户满意度为目的,建立了第三方物流企业客户满意度评价指标体系,采用粒子群优化算法对支持向量机的参数进行优化,最终用支持向量机对第三方物流企业客户满意度进行评价。实验结果表明,优化参数后的支持向量机对客户满意度进行分析时可得到精度较高的结果,对第三方物流企业的客户满意度评价具有较强的实际意义。

The paper builds a customer satisfaction evaluation index system for third -party logistics companies for the purpose of providing standardized,professional and personalized service to customers so as to improve customer satisfaction.It uses PSO to optimize parameters of SVM.And finally uses the SVM to evaluate customer satisfaction of third -party logistics companies.The experimental results show that when the method of SVM after parameter optimization is applied to analyze the customer satisfaction,it can come to a high precision result.Therefore,the method has a strong practical significance for customer satisfaction evaluation of third -party logistics companies.