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Full Description
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.
Contents
.- 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.
