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List of contents
.- Intelligent Data Analysis amp Prediction.
.- MSFformer: Multi-Scale Spatiotemporal Fusion Transformer with Preserving Non Stationary Information for Time Series Forecasting.
.- Quantifying the Impact of Coaching Effectiveness Based on the TEL Model.
.- SSF-GCN: Sensor-Spatial Fusion Graph Network for RUL Prediction.
.- AW-SARIMA: Efficient Hybrid Framework for Nonstationary Time Series Forecasting via DWT and Adaptive Thresholding.
.- Research on Intelligent Evaluation Model Based on Large Models.
.- Learner Empowered Knowledge Tracing Model.
.- A Few-Shot Intrusion Detection Method Combining Model-Agnostic Meta-Learning And Siamese Neural Network.
.- How to Use Social Media for Bitcoin Price Prediction: A Multi-Source Data Fusion Method Based on CSTNet.
.- CMulti-Feature Fusion Method for Programming Exercise Difficulty Assessment Using CodeBERT.
.- Scene Graph-based Semantic Enhancement for Multimodal Fake News Detection.
.- IDMixer: Decomposition Spatial-Temporal Identity for Traffic Flow Forecasting.
.- A Self-Attentive Temporal-Spatial Anomaly Detection Method for IoT Time Series.
.- Adaptive Cross-Variable Spectral Filtering for Time Series Forecasting .
.- Hybrid Car-Following Model with LSTM and RF in Driver Behavior.
.- A Mixture-of-Experts Framework with Fake Review Detection for Robust Recommendation Systems.
.- Multi-scale Dual-path Transformer Network for Multivariate Time Series Forecasting.
.- BFKT: Enhancing Knowledge Tracing based on Forgetting Mechanisms and Multi Feature Fusion.
.- Macro-Micro Feature Aware Transformer for Dissolved Oxygen Prediction.
.- MTDTSN: Multi-Scale Spatiotemporal Networks with Exogenous Factors for Bus Passenger Flow Prediction.
.- AMSformer: Adaptive Transformer with Convolutional Multi-scale Feature Interaction for Time Series Forecasting.
.- A Time-Enhanced Data Disentanglement Network for Traffic Flow Forecasting.
.- CycleKAN: Integrating Kolmogorov-Arnold Networks with Explicit Cycle Modeling for Efficient Urban Traffic Forecasting.
.- Capability-Aware Knowledge Tracing for Learner’s Knowledge Mastery Modeling.
.- AGTCN: An Adaptive Gating Approach in Spatiotemporal Convolutional Networks for Accurate Air Quality Prediction.
.- TrafusionNet: Efficient Multi-Agent Trajectory Prediction with Temporal-Social Perception Mamba and Diffusion Model.
.- FedVCP: Efficient Crowd Flow Prediction Employing Multi-Source External Factors in Vertical Federated Learning.
.- Shareformer: A Patch Transformer Model with Shared Attention for Multivariate Time Series Forecasting.
.- A Novel Random Sample Partition-Based Ensemble Algorithm for Credit Card Fraud Detection.
.- StarHAR: A Lightweight and Low-latency Framework for Sensor-based Human Activity Recognition.
.- Trend Prediction First, Personality Refinement After. KanPaTST: A KAN Fine tuned Patch Time Series Transformer for Public Opinion Popularity Forecasting.
.- CEDMix: Contrast-Enhanced Dynamic Channel Mixing for Correlated Time Series Forecasting.
.- NuPreX: Times Series Forecasting for The Nuclear Steam Supply System.
.- Frequency-Aware Robust Multimodal Fake News Detection.
.- Sample Spatial Distribution and Diffusion Time Deviation Based Anomaly Detection Method.
.- Building Extraction from Remote Sensing Images Based on Dual-Stream Feature Fusion Network.
.- Multi-Hop Aware Graph Convolutional Network and Collaborative Transformer for Traffic Flow Prediction.
.- Multi-step Traffic Flow Prediction Based on Reinforced Attention Graph Convolutional Network.
.- CDFNet: Collaborative Decomposition and Forecasting Network for Time Series.
.- S³E-Net: Spatio-Temporal Selective State Expert Network for Traffic Flow Prediction.
.- ECDformer: Enhanced Channel-Dependent Transformer for Multivariate Time Series Forecasting.
.- Rule Generation for Anomalous Behaviors Detection in Enterprises: A Few-Shot Learning Approach via Chain-of-Thoughts.
.- TVCorNet: Time-Variable Correlation Learning Enhancement Network for Multivariate Time Series Forecasting.
.- BiMa-Former: A Dual-Token Hybrid Model with Bidirectional Mamba and Transformer for Temporal- Multivariate Decoupled Forecasting.
Summary
This 20-volume set LNCS 15842-15861 constitutes - in conjunction with the 4-volume set LNAI 15862-15865 and the 4-volume set LNBI 15866-15869 - the refereed proceedings of the 21st International Conference on Intelligent Computing, ICIC 2025, held in Ningbo, China, during July 26-29, 2025.
The total of 1206 regular papers were carefully reviewed and selected from 4032 submissions.
This year, the conference concentrated mainly on the theories and methodologies as well as the emerging applications of intelligent computing. Its aim was to unify the picture of contemporary intelligent computing techniques as an integral concept that highlights the trends in advanced computational intelligence and bridges theoretical research with applications. Therefore, the theme for this conference was "Advanced Intelligent Computing Technology and Applications".
