Analysis and Prediction Model of Mobile User Experience Based on PCA Principal Component Analysis and BP Neural Network

The rapid evolution of mobile communication technology, network construction, and coverage improvement underscores the importance of customer satisfaction for major operators in today's transparent and homogenous product market. This model integrates customer preferences, habits, and network performance data to enhance personalized services, predict issues, and proactively improve network quality. The analysis reveals key factors affecting customer satisfaction in voice and internet services, employing principal component analysis. The second part employs a BP neural network model to predict user scores for voice and internet services, optimizing accuracy through data preprocessing and normalization. The results indicate promising correlation coefficients and mean square errors. Practical considerations for data quality, model parameters, and ongoing improvements are discussed, suggesting future research directions.