| Summary: | The global concern for environmental protection has driven the demand for corporate environmental accounting information, especially in heavily polluting industries. Currently, there are deficiencies in China's research on environmental accounting information and its institutional development, and there is an urgent need for improved evaluation systems and models. The study proposes the RAGA-PP model, which is an environmental accounting information disclosure evaluation model that combines accelerated genetic algorithm and projection tracing algorithm. The model is based on 28 secondary evaluation indicators and aims to optimize the projection tracing through the accelerated genetic algorithm with real number coding to improve the stability and accuracy of data analysis. The experiment proves that the evaluation error value of the RAGA-PP model is 3.45 % on average, which is significantly lower compared to 9.55 % of the ant colony algorithm. The results show that the RAGA-PP model has significant advantages in accurately evaluating the quality of corporate environmental information disclosure, which confirms its application value in environmental accounting information disclosure in heavy pollution industries. The purpose of the study is to promote the improvement of the environmental accounting information disclosure system and to provide support for enhancing corporate environmental awareness and social responsibility.
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