Abstract
This work aims to solve the complex problems of non-linearity, instability, and multiple economic factors in the tax forecast of the ceramic industry to ensure the sustainable development of the ceramic industry. The key influential indicators of the tax forecast are obtained by analyzing the principal components affecting the tax index. In addition, a human-computer interaction (HCI) system is established based on cognitive psychology theory to improve the user-friendliness of tax analysis. At the same time, the tax data of the ceramic industry in Jingdezhen City, Jiangxi Province in different years are used for the empirical analysis of the tax prediction of different prediction models, including particle swarm optimization (PSO) algorithm, and fusion algorithm (FA), and support vector machine (SVM). This work comprehensively analyzes the influence of the optimized tax supervision mode on the economic development of the ceramic industry and provides ideas for the development of the ceramic industry in Jingdezhen. The research results demonstrate that the main indicator affecting tax revenue is the added value of the primary and secondary industries. The optimized SVM based on grid search method can provide a comprehensive data base for tax forecasting. The optimization of the computer system based on cognitive psychology improves the model prediction accuracy by 10%, and the absolute error decreases from 6.9 to 1.8%. The tax forecast results indicate that the tax imbalance in Jingdezhen is increasing. Therefore, the government needs to attach great importance to the development of the ceramic industry and strictly implement the tax policy. The tax supervision model can alleviate the problems of low fiscal contribution rate, tax evasion, and management loopholes. In addition, the SVM tax prediction model optimized by grid search method will lay a theoretical foundation for the research and application of taxation in the ceramic industry.
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