Analysis and Application Research of E-Commerce Financial Management Based on T-DPC Optimization Algorithm

被引:0
|
作者
Wang Y. [1 ]
Shan Y. [2 ]
机构
[1] Accounting Department, North China Institute of Science and Technology, Langfang
[2] School of Emergency Technology & Management, North China Institute of Science and Technology, Langfang
关键词
Clustering; DPC; Financial data; Prediction; T-SNE;
D O I
10.31181/dmame722024943
中图分类号
学科分类号
摘要
Given the intricate, multifaceted nature of financial data in e-commerce enterprises, this article presents a T-DPC algorithm for analyzing financial management in these businesses. The algorithm utilizes the t-SNE method to reduce the dimensionality of financial data, whilst also implementing an enhanced DPC algorithm based on the K-nearest neighbor concept to analyze financial data clusters. The results show that the F-measure metrics of the DPC algorithm optimized by t-SNE improve 16.7% and 3.07% over the DPC algorithm after testing on the PID and Wine datasets, and its running time is faster than the DPC algorithm on the Aggregation, D31, and R15 datasets by 16.2. Therefore, the algorithm has reference significance for the financial analysis of e-commerce enterprises. © 2024 Regional Association for Security and crisis management. All rights reserved.
引用
收藏
页码:119 / 131
页数:12
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