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This three-volume set CCIS 2213-2215 constitutes the refereed proceedings of the 10th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2024, held in Macau, China, during September 27–30, 2024.
The 74 full papers and 3 short papers presented in these three volumes were carefully reviewed and selected from 249 submissions.
The papers are organized in the following topical sections:
Part I: Novel methods or tools used in big data and its applications; applications of data science.
Part II: Education research, methods and materials for data science and engine; data security and privacy; big data mining and knowledge management.
Part III: Infrastructure for data science; social media and recommendation system; multimedia data management and analysis.
.- Novel methods or tools used in big data and its applications.
.- Quantitative Analysis of the Factors Influencing Macao's Tourism Industry: A Gray Correlation Approach.
.- Multi-AUV Hunting Strategy Based on the Lions Group Algorithm.
.- Study on the Coupled and Coordinated Relationships between Social Security and Economic and Social Development in Macao.
.- A Segmentation Network for Coastal Cegetation Guided by Category-Wighted Information from UAV Perspective Based on SAM.
.- GAN-Based Defogging and Multiscale Fusion Approach for UAV-Based Seagrass Bed Imagery Semantic segmentation in challenging marine environments.
.- SEBWatcher: Visual Analysis System for Subject, Environment and Behavior in Traffic Scenes.
.- Research on the Promotion and Enhancement Paths of Hainan Wenbifeng Pangu Cultural Tourist Areas Based on Network Text Analysis.
.- Based on Network Text Analysis: A Study on the Promotion Strategy of a Boundary Island for Lingshui Tourism Experience.
.- Deep Reinforcement Learning Based on Greed for the Critical Cross section Identification Problem.
.- Intrusion Detection Based on Feature Selection and Transformer BiGRU.
.- Discussion on the construction of power 3D design platform for nested virtualized hybrid cloud.
.- Applications of Data Science.
.- Application of Deep Learning Models Based on Chaos Modeling in Power Internet of Things Forecasting Tasks.
.- Study on compatibility of vegetable insulating oils and mineral insulating oils for transformer based on molecular simulation methods.
.- Collaborative optimization scheduling model for clean energy in microgrid clusters.
.- A Distributed Multi-Microgrid Intelligent Scheduling for New Power System.
.- Development and Application of Intelligent Calculation Analysis Platform For Large Power Grid.
.- A Deep Reinforcement Learning Control Strategy with Integrated Droop Control for Parallel DC-DC Buck Converters with CPLs.
.- MST: A Comprehensive Approach for Short-Term Power Load Forecasting Based on Data Decomposition, Local and Global Modeling.
.- An Approach to Identification Model for Electric Event Based on Clustering Analysis.
.- Research on Prediction Models and Optimization Methods for Electrical Current Consumption of Users.
.- Re-GNN: ANewModelforPredicting Circuit Reliability Degradation.
.- TRANSFORMER OIL TEMPERATURE PREDICTION METHOD BASED ON CAUSAL DISCOVERY AND GNN-LSTM MODEL.
.- The Electronic Power Data Traceability Model Based on Hybrid Consensus and IPFS.
.- Research on complementation of new energy spot and medium to long-term transactions based on blockchain·
.- Knowledge-driven Calculating Method for Transmission Section Limit of Large Power Grid.
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