Intelligence Computation and Applications
Description
This two-volume set, constitutes the revised selected papers of the 16th International Symposium on Intelligence Computation and Applications, ISICA 2025, held in Guangzhou, China, during November 15-16, 2025.
The 63 full papers included in these proceedings were carefully reviewed and selected from178 submissions. They were organized in the following topical sections:
Part I : Frontiers of Evolutionary Intelligent Optimization Algorithms; Intelligent Systems and Detection Technology.
Part II : Exploration of Computer Vision; Machine Learning and Its Applications; AI Empowering Education and Design Innovation.
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Content
.- Frontiers of Evolutionary Intelligent Optimization Algorithms.
.- Model construction of time decay function based on genetic programming .
.- A Frequency Domain Search-based Multi-objective Evolutionary Algorithm for Solving Large-scale Multi-objective Optimization Problems.
.- Dual-Space Dynamic Feedback Mechanism for Multi- Task Evolutionary Algorithm.
.- An interval-parameter multi-objective evolutionary algorithm with marginal probability dominance.
.- A multi-criteria hydropower station site selection model based on reinforcement learning enhanced particle swarm optimization.
.- A Dimensionality Reduction Algorithm Based on Population Decomposition and Statistical Analysis of Non-Redundant Objective Preferences.
.- Set Transformer Guided NSGA-III for Large-Scale Multi-Objective Optimization.
.- MOEA/D-TA: Subproblem-Aligned Transformer for Large-Scale Multi-objective Optimization.
.- A Framework for Large-Scale Multi-Objective Optimization Driven by VAE-Based Manifold Learning.
.- UMGS-MOEA: A Multi-objective Evolutionary Algorithm Based on UMAP and Manifold-Guided Search.
.- A GEP-based Modeling Approach for Human Identification Using 3D Skeletal Data.
.- A Frequency Domain Search-based Multi-objective Evolutionary Algorithm for Solving Large-scale Multi-objective Optimization Problems.
.- Multi-Objective Evolutionary Algorithm with Dynamically Changing Objective Functions.
.- Research on Grade Recognition and Classification of Wild Peaches Based on ResNet and Transfer Learning.
.- Multi-Objective Evolutionary Algorithm with Dynamically Changing Objective Functions.
.- Evaluation of Internet Teaching Quality: Application of Evidence Theory and Neural Network Model.
.- UMGS-MOEA: A Multi-objective Evolutionary Algorithm Based on UMAP and Manifold-Guided Search.
.- Interval Multi-Population Evolutionary Algorithm for Service Deployment and Task Offloading in Edge Environments.
.- An Expensive Interval Many-objective Optimization Algorithm Based on Indicators.
.- UMGS-MOEA: A Multi-objective Evolutionary Algorithm Based on UMAP and Manifold-Guided Search.
.- Intelligent Systems and Detection Technology.
.- Iterative Disturbance Observer-based Data-Driven Adaptive Iterative Learning Control.
.- Research on Multi-Face Mask Recognition Based on MTCNN Algorithm And SVM.
.- Boosting the Adversarial Robustness for Object Detection via Adaptive Perturbation Control.
.- State-Based Hiding Privacy for Location-Based Services.
.- Adaptive Oversampling by Combining Sample Local Density with Position Information for Imbalanced Data Classification.
.- Multi-Modal Intelligent Algorithm for Identifying the Effectiveness of Computer Behaviors.
.- Research on a Real-Time Analysis Platform for Equipment Operational Status in Smart Manufacturing.
.- A Multimodal Data-Based Intelligent Diagnosis and Treatment System for Colorectal Cancer TNM Staging.
.- A Fall Detection Method Using Radar and Infrared Heterogeneous Fusion.
.- Maintenance Strategy Recommendation for Wireless Sensor Networks.
.- Analysis of Spatial Misalignment and Power Transfer Efficiency in Magnetic-Resonant Wireless Power Transfer Systems with Parallel-Axis Coils.