Research on Quality Evaluation of Online Reservation Hotel APP Based on a RBF Neural Network and Support Vector Machine

M. Xiang
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引用次数: 1

Abstract

In order to evaluate the quality of online reservation hotel APP, RBF neural and support vector machine are used to evaluate the quality of online reservation hotel APP. First, the basic theory of the RBF neural network is studied, and the training algorithm of the RBF neural network is designed. Second, the basic model of support vector machine is analyzed, and the training algorithm is designed. Third, the evaluation index system of online reservation hotel APP is designed, and the weight of every index is established based on questionnaires and expert interview, and the evaluation simulation is carried out for 25 online reservation hotel APP, results show that the RBF neural network and support vector machine can obtain consistent evaluation results, and the support vector machine has better evaluation performance.
基于RBF神经网络和支持向量机的在线预订酒店APP质量评价研究
为了评价在线预订酒店APP的质量,采用RBF神经网络和支持向量机对在线预订酒店APP的质量进行评价。首先,研究了RBF神经网络的基本理论,设计了RBF神经网络的训练算法;其次,分析了支持向量机的基本模型,设计了训练算法;第三,设计了在线预订酒店APP的评价指标体系,并基于问卷调查和专家访谈建立了各指标的权重,对25个在线预订酒店APP进行了评价仿真,结果表明RBF神经网络和支持向量机能够获得一致的评价结果,支持向量机具有更好的评价性能。
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