Research on the Application of Big Data Deep Learning Algorithms in Management Accounting

Design management is an important part of data analysis, and it is also the main aspect of economic management of enterprises. Big data can provide qualifications for accounting management, so it has great potential for development.The applied research is critical in intelligent management accounting, however it has an issue with erroneous performance positioning. The typical Neural network algorithms is unable to address the inaccurate application positioning issue in intelligent management accounting, and the result is insufficient. As a result, a Big data deep learning algorithms-based application research in management accounting is provided, and application research in management accounting is assessed. To begin, the gradient descent theory is used to discover the influencing elements, and the indicators are split based on the applied research’s needs to decrease interference factors in the applied research. The gradient descent theory is then used to create a Big data deep learning algorithms applied research accounting table, and the outcomes of the applied research are thoroughly examined. The MATLAB simulation results reveal that, under particular evaluation conditions, the Big data deep learning algorithms outperforms the standard Neural network algorithms in terms of applied research accuracy and time of influencing variables. The method can improve the overall level of accounting management, with an increase of between $10 \%$ and $20 \%$. Therefore, the big data analysis method can meet the requirements of equipment analy sis and management.