A Data Technology Oriented to Information Fusion to Build an Intelligent Accounting Computerized Model

Xu, Ziyan; Zhou, Wenxue

doi:10.1155/2021/6031324

Cited by 7 publications

(4 citation statements)

References 21 publications

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“…After preparing a relatively "clean" dataset, it is necessary to perform feature engineering to construct various financial metrics [6] required for analysis. For instance, if you want to predict the sales volume and sales revenue of a product, you can construct features based on the sales data from the past 6 months, create a time series using sales data from the same period over the past 3 years, and incorporate features like average selling price and promotional efforts.…”

Section: Feature Engineering and Metric Constructionmentioning

confidence: 99%

Enterprise Financial Accounting Information Management System based on Big Data Mining

Feng,

Feng

2024

Proceedings of the 4th International Conference on Informatization Economic Development and Management, IEDM 2024, February 23–

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Enterprise financial accounting, in the face of distributed and heterogeneous financial accounting data, effective aggregation and mining for data-driven management decisions are important means for fine-grained enterprise control. This paper studies the method of constructing an intelligent management system for enterprise financial accounting based on the concept of big data. First, the business process is analyzed to clarify data collection interfaces and quality control mechanisms. Then, time series analysis, association rules, and machine learning prediction algorithms are integrated to establish analytical models that match business objectives. Based on this, a process-oriented and service-oriented system framework is designed to achieve unified integrated access to multi-source data and model analysis services. Experiments show that the system can effectively discover relationships between data and time series change patterns, perform sales forecasting, anomaly detection, and more, demonstrating its support in practical procurement planning and marketing decisions, validating the effectiveness of the system design. This research provides a positive practical exploration for the construction of an intelligent enterprise financial accounting management system.

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Section: Feature Engineering and Metric Constructionmentioning

confidence: 99%

Enterprise Financial Accounting Information Management System based on Big Data Mining

Feng,

Feng

2024

Proceedings of the 4th International Conference on Informatization Economic Development and Management, IEDM 2024, February 23–

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“…In order to avoid overfitting and improve the processing speed, the fully connected layer is replaced by the GAP layer and finally connected to the softmax layer [63][64][65][66]. The input is the fused features processed by the DBM layer, and the output is the classification and probability of emotional affiliation by the softmax layer.…”

Section: Speech Modal Designmentioning

confidence: 99%

An Artificial Intelligence-Based Approach to Social Data-Aware Optimization for Enterprise Management

Zhang

2022

Wireless Communications and Mobile Computing

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Enterprise management has always been a hot issue in society. In today’s society, enterprises are no longer individuals cut off from society and no longer have profit as their sole purpose, but need to exist and develop in combination with social information. With the increasing competition among enterprises, the original enterprise management methods can no longer meet the needs of sustainable development of enterprises, nor can they effectively utilize social data. To better understand the daily emotions of corporate workers, we use a multimodal emotion recognition method in this paper. Multimodal emotion recognition refers to the recognition of human emotional states through different modal information such as speech, visual, and text related to human emotional expressions, which has important research significance in the fields of human-computer interaction, artificial intelligence, and emotional computing and has received much attention from researchers. Given the great success of deep learning methods developed in recent years for various tasks, various deep neural networks are now used to learn high-level representations of emotional features for multimodal emotion recognition. The analysis of employee sentiment is complemented by traditional management methods that make full use of social data. In this paper, based on the study of a single enterprise management model, the proposed model contains five substructure modules, starting with feature inputs, extracting features at different levels through three convolutional modules and outputting recognition results through a softmax classifier. The focus is on how to utilize social data, while combining deep learning with traditional enterprise management methods to fill the research gap in this area in academia.

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“…With the popularization of artificial intelligence, basic accounting work will be completely replaced by financial robots, financial robots can be more efficient than human beings in completing the entry of financial data, account processing, and other cumbersome, mechanical, highly repetitive financial accounting work, and the accuracy rate is much higher than human beings. In the face of the comprehensive application of artificial intelligence in the field of finance, basic accounting practitioners will face a huge challenge and ultimately force basic accounting practitioners to manage decision-making accounting and information technology accounting transformation [4][5]. The era of artificial intelligence is causing a shortage of composite accounting talents with management decision-making and information technology abilities.…”

Section: Introductionmentioning

confidence: 99%

Artificial Intelligence Technology Empowers Practical Teaching of Higher Vocational Accounting Majors

Wu,

Chen,

Zhang

et al. 2024

Applied Mathematics and Nonlinear Sciences

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This paper proposes an interactive study of online practice teaching based on LightGBM model. To avoid the overfitting of training data by LightGBM model, the objective function of LightGBM model is derived utilizing GBDT gradient boosting tree to optimize the overfitting problem of training data. Based on the interactive study of online practice teaching based on the LightGBM model, the construction of the accounting practice teaching system is completed by using B/S mode, and the simulation analysis of online practice teaching of accounting majors in the context of the artificial intelligence era is carried out. The results show that the students in class C, with an AUC value of 0.819, are higher than that before optimization by 0.095, and similarly comparing the AUC values of other classes are higher than that before optimization. The LightGBM model optimized by the grid search algorithm can effectively identify and interact with students’ accounting practice behavioral characteristics, and to a certain extent, effectively predict students’ accounting practice ability. This study has the potential to guide students in mastering accounting practice knowledge, guaranteeing quality practice teaching, and fostering the growth of accounting professionals.

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A Data Technology Oriented to Information Fusion to Build an Intelligent Accounting Computerized Model

Cited by 7 publications

References 21 publications

Enterprise Financial Accounting Information Management System based on Big Data Mining

Enterprise Financial Accounting Information Management System based on Big Data Mining

An Artificial Intelligence-Based Approach to Social Data-Aware Optimization for Enterprise Management

Artificial Intelligence Technology Empowers Practical Teaching of Higher Vocational Accounting Majors

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