Abstract
The development of information technology has made the traditional financial management model of power supply enterprises unable to meet the needs of modern enterprises for data processing and decision support. The study aims to implement a financial information software system for power supply companies built on the Java 2 Platform Enterprise Edition (J2EE) framework, thereby enhancing the precision of financial data processing. This study proposes financial information mining based on an improved Apriori algorithm and designs and implements a software system under the J2EE framework. The improved Apriori algorithm improves the efficiency of the data mining process by introducing a dynamic update mechanism and updating frequent item sets only when necessary. The algorithm also adopts parallelization processing technology to accelerate the generation of frequent item sets and the extraction of association rules through distributed computing resources. The results indicated that the designed system could effectively mine frequent itemsets and association rules in financial data, and outperformed existing systems in key performance indicators such as CPU usage and system throughput. The CPU usage remained between 40% and 60%, and the throughput was roughly around 30 Mb/s, while the CPU usage of other systems fluctuated between 20% and 80%, with throughput increasing from nearly 10 Mb/s to nearly 30 Mb/s. In addition, the system response time has been significantly reduced, and the data accuracy has reached 99.9%. The financial information software system for power supply companies based on the J2EE framework can effectively support the financial decision-making and management of power supply companies. This is crucial for promoting the informatization process of enterprises, which can strengthen the informatization level of the entire energy industry and provide valuable experience for other enterprises in the same industry.
Highlights
This research system is based on J2EE framework and improved Apriori algorithm to improve the efficiency of financial data mining.
The system performs outstandingly in terms of performance, with stable CPU usage, short response time, and data accuracy as high as 99.9%.
This system has optimized the financial management process and promoted the informatization development of the industry.
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Details
1 Henan Institute of Technology, Xinxiang, China (GRID:grid.503012.5)




