Data Visualization Intelligent Analysis Model in Human Resource Management

A HR Data Visualization Intelligent Analytical Model is presented, which is designed to provide more direct and precise support to HR decision making. In this model, an improved PSO and Deep Belief Network (IPSO-DBN) is introduced, and the PSO is used to optimize the parameters of the deep belief network. The experiment uses human resource data from a large enterprise in the past 5 years, covering employee basic information, performance evaluation, training records, and resignation data. The IPSO-DBN algorithm is compared with traditional algorithms such as BP neural network and support vector machine. The results show that the IPSO-DBN algorithm has an accuracy rate of 92.5% in employee performance prediction and an accuracy rate of 88.3% in turnover tendency prediction, which are significantly higher than other comparison algorithms. In terms of data visualization, tools such as Echarts are used to realize multi-dimensional visualization of employee performance distribution, training needs analysis, etc., so that managers can quickly gain insight into human resource status.