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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.<\/jats:p>","DOI":"10.1186\/s42162-024-00366-8","type":"journal-article","created":{"date-parts":[[2024,8,6]],"date-time":"2024-08-06T11:02:11Z","timestamp":1722942131000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Design and optimization strategy of electricity marketing information system supported by cloud computing platform"],"prefix":"10.1186","volume":"7","author":[{"given":"Bo","family":"Chen","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wei","family":"Ge","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,8,6]]},"reference":[{"issue":"1\u20132","key":"366_CR1","doi-asserted-by":"publisher","first-page":"119","DOI":"10.1007\/s00170-021-07324-8","volume":"118","author":"V Afanasyev","year":"2022","unstructured":"Afanasyev V, Chernyshenko V, Kuzmin V, Voronin V, Mkrttchian V (2022) Advanced information technology for development of electric power market. 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