The Use of BP Neural Network Algorithm and Natural Language Processing in the Impact of Social Audit on Enterprise Innovation Ability

Abstract

At present, there are still some problems in the document management of enterprise innovation projects, such as non-standard management, lagging update, chaotic content, insufficient information, and insufficient application. There is still a lack of effective methods to evaluate the financing ability of enterprises. To solve the above problems, high technology expertise (HNTE) is taken as the research objects. Firstly, the relationship between social audit and enterprise technological innovation is analyzed, and on this basis, combined with natural language processing (NLP), an extraction method of project document information is proposed. Secondly, the evaluation index system of enterprise financing ability is constructed based on Back Propagation Neural Network (BPNN), and the technology innovation audit system of HNTEs. Finally, combined with the actual content, the proposed document audit method is evaluated. The results show that: the average accuracy rate of the NLP-based innovation project document audit method is 91.36%, the average recall rate is 96.34%, and the average F statistical value is 95.34%. Among them, the recall rate and F statistical value are about 2.3% and 1.4% higher than manual processing, respectively. The recall rate and F value are obviously better than those of manual processing methods, and the processing time of single document based on NLP is only 87.5 s. The processing time is nearly 50 times lower than that of manual processing, which greatly improves the processing efficiency of document information. The corresponding test results of each index selected based on the evaluation of enterprise financing ability are all below 0.1, which meets the requirements of consistency. The evaluation results of BPNN model on enterprise financing ability are highly consistent with the target value, and the prediction error is controlled within 0.02, which can provide more accurate prediction results. This research obtains a more accurate prediction model of enterprise financing ability evaluation, which provides technical support for social auditing and the innovation and development of enterprise technology, and provides a feasible route for the development of BPNN in the financial field.

Big Data Model of Digital Employees of High-Tech Enterprises under the Background of Digital Transformation

“…For example, companies can rely on the company's procurement channels, distribution systems, and terminal network advantages and use digital technology to eliminate information between upstream and downstream enterprises in the supply chain. Asymmetric tangerine is innovating the supply chain service model and improving the circulation efficiency of the supply chain; on the other hand, it extensively collects and stores consumer group information and conducts in-depth analysis to form 8 Scientific Programming customer portraits and implement precise marketing, thereby improving labor production efficiency, reducing operating costs, management costs, and investment costs, and improving enterprise performance and sustainable competitiveness, based on long-term development [22][23][24][25][26][27][28]. Finally, strengthen government governance, and distribute government subsidies in a reasonable and targeted manner.…”

Transformation of artificial intelligence in the Accounting Profession toward a New Technology Era

“…Furthermore, NLP also provides sentiment analysis tools contained in the audit text. For example, analysis in financial statements or management reports using NLP can help identify whether the text is positive, negative, or neutral to the performance of the company or entity being audited [20]. Another advantage of utilizing NLP in the audit process is that it helps in understanding the context around words or phrases in audit documents.…”

“…Another advantage of utilizing NLP in the audit process is that it helps in understanding the context around words or phrases in audit documents. This can help differentiate the use of the same words in different contexts and explain relationships between entities, transactions, or events in documents, as well as ensure consistent use of terminology and concepts in audit documents, which can improve data clarity and interpretation [20]. The process helps in extracting hidden data in the audit text, such as patterns or trends that may not be immediately visible to the auditor.…”

Result Prediction of Wordle Word Guessing Game Based on SVM And BP Neural Network Multi-Input-Multi-Output Regression Prediction Model

“…BP-neural network [9] is an artificial neural network with back propagation function, which is composed of input layer, output layer and hidden layer. The hidden layer often has several layers [10].…”