云计算平台支持下的电力营销信息系统设计与优化策略

Q2 Energy
Bo Chen, Wei Ge
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引用次数: 0

摘要

本文深入探讨了电力营销信息系统的综合需求分析、设计实现、算法优化和实验评估,旨在构建一个高效、安全、人性化的现代信息系统。在需求分析阶段,强调了业务流程优化、数据管理分析、安全合规性、系统集成和可扩展性的重要性,同时考虑了终端客户的多样化需求。在设计和实现部分,系统架构基于微服务和云原生技术,确保高性能和安全性;通过 Spring Boot、Vue.js 等技术栈实现模块化开发。在算法优化方面,通过集成学习和自编码器相结合的方式,采用 LSTM 进行电力需求预测和异常检测,提高了预测精度和异常识别能力。实验评估表明,该系统在云计算环境下表现出良好的性能、安全性和可扩展性,成本效益明显优于传统部署方式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Design and optimization strategy of electricity marketing information system supported by cloud computing platform

This paper provides an in-depth discussion on the comprehensive requirements analysis, design implementation, algorithm optimization, and experimental evaluation of an electric power marketing information system, aiming to build a modern information system that is efficient, secure, and user-friendly. In the requirements analysis phase, the importance of business process optimization, data management analysis, security compliance, system integration and scalability is emphasized, while the diversified needs of end customers are considered. For the design and implementation part, the system architecture is based on microservices and cloud-native technologies to ensure high performance and security; and modularized development is achieved through Spring Boot, Vue.js and other technology stacks. For algorithm optimization, LSTM is used for power demand prediction and anomaly detection by combining integrated learning and self-encoder, which improves the prediction accuracy and anomaly identification capability. Experimental evaluation shows that the system demonstrates good performance, security and scalability in cloud computing environment, and the cost-effectiveness is significantly better than traditional deployment.

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来源期刊
Energy Informatics
Energy Informatics Computer Science-Computer Networks and Communications
CiteScore
5.50
自引率
0.00%
发文量
34
审稿时长
5 weeks
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