Advances and Trends in Artificial Intelligence. Theory and Applications

38th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2025, Kitakyushu, Japan, July 1-4, 2025, Proceedings, Part I
Herausgegeben:Fujita, Hamido; Watanobe, Yutaka; Ali, Moonis; Wang, Yinglin

• Broschiertes Buch

Produktbeschreibung

This book constitutes the refereed proceedings of the 38th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems on Advances and Trends in Artificial Intelligence, IEA/AIE 2025, held in Kitakyushu, Japan, in July 1 4, 2025.

The 80 full papers and 9 short papers included in this book were carefully reviewed and selected from 130 submissions. They focus on the following topical sections:

Part I: Reinforcement Learning; Optimization; Natural Language Processing; Multi-Agent; Machine Learning and Decision Making; Knowledge Representation; Data Engineering; Large Language Model; Computer Vision.

Part II: Robotics; Education; Cyber Security; Healthcare and Medical Applications; Advanced Applied Intelligence Methodologies and Applications; Intelligent Systems and e-Applications; Industrial and Engineering Applications.

Produktdetails

• Lecture Notes in Computer Science 15706
• Verlag: Springer / Springer Nature Singapore / Springer, Berlin
• Artikelnr. des Verlages: 978-981-96-8888-3
• Seitenzahl: 564
• Erscheinungstermin: 1. Juli 2025
• Englisch
• Abmessung: 235mm x 155mm x 31mm
• Gewicht: 844g
• ISBN-13: 9789819688883
• ISBN-10: 9819688884
• Artikelnr.: 74304882

Inhaltsangabe

.- Reinforcement Learning.

.- An Enhanced Preference-Based Reinforcement Learning Framework for Autonomous System.

.- Reinforcement Learning based Iterated Greedy for Parallel Machine Scheduling with Weighted Earliness Tardiness.

.- VMD-IMF Enhanced Hyper Graph Attention Module Based Reinforcement Learning For Portfolio Optimization.

.- A reinforcement learning based framework to the facility layout problem.

.- Optimization.

.- Bayesian Optimization for Fine-Tuning an AI Solver: Application to Preventive Maintenance Scheduling Problems.

.- Domain Generalization through Domain-Expert Risk Assessment.

.- Enhanced Optimization Space Learning: Towards Real-Time Compiler Optimization.

.- Optimizing Feature Selection Binary Peacock Algorithm with improved movement strategy.

.- Natural Language Processing.

.- Apply TF-IDF and LDA to Explore Topics and Related Trends in Electric Vehicle Reviews.

.- Identifying Fake Reviews and Their Implications Using BERT and LDA: A Case Study of Online Shopping Website Reviews.

.- A Lightweight and Efficient Punctuation and Word Casing Prediction Model for On Device Streaming ASR.

.- SYNCAD: Synchronised Yields from Narrative Cross Modal Audio and Data.

.- MultiGAU: Real Time Sign Language Generation using Multimodal Gated Attention.

.- Classification of Approval Desires and Analysis of Emotional and Linguistic Features in SNS Posts Using Generative AI.

.- Multi-Agent.

.- Hierarchical Multi-Agent Reinforcement Learning with Epistemic Priors for Scalable Communicationless Coordination of Teamable Agents.

.- DynaMIX: Sample-Efficient Multi Agent Reinforcement Learning with Multi-Step Temporal Forward Dynamics Modeling.

.- Automated Issue Hierarchy Generation for Improved Automated Negotiation Outcomes.

.- Machine Learning and Decision Making.

.- Distribution Variance for Surrogate Weights in Multi-Criteria Decision Analysis.

.- Bridging the Trust Gap: Leveraging Explainable AI for Personalized E-Commerce Recommendations.

.- A clustering method based on hesitant difference granularity.

.- Evaluation of Efficient AI for the Edge: Insights from Deep Neural Networks Model Compression Techniques Applied to Occupancy Detection.

.- LSTM-based Proactive Scheduling of Stream Applications in Edge/Cloud Environments.

.- Uncertainty Quantification Of Multimodal Models.

.- Knowledge Representation.

.- Automating OntoClean Ontology Verification.

.- Automating OntoClean - Subsumption Hierarchy Construction.

.- Possibilistic Reasoning with Fuzzy Formal Contexts: An Extended Abstract.

.- A Strategy for Implementing Garbage Detection in Ontology Completion using Description Logics.

.- Data Engineering.

.- Uncertainty-based Instance-Dependent Noisy Label Datasets Generation.

.- Guided by Uncertainty: Semi-supervised Domain Adaptation with Curriculum and Contrastive Learning.

.- Linking Data Meaningfully: Identifying Meaningful Keys and Foreign Keys from Data.

.- CAMI: A missing value imputation method based on causal discovery and self-attention.

.- MDR: An Ontology Vocabulary and Registry Service for Dataset Catalogs.

.- A-REACT: Adaptive Resampling and Active Classification for Thresholded Anomalies.

.- DistResampleR-Lite: Light Distributed Resampler for Imbalanced Regression Problems.

.- Fast HSIC-based tests for random processes.

.- Large Language Model.

.- Exploring the Efficacy of Large Language Models in Predicting Chemical Toxicity.

.- Towards Predicting Complex Carpooling Trajectories with Context-Augmented BERT LLM in Chaotic Environments.

.- LLM-base MaSE, A Software Development Framework for Developing Multi-Agent Systems.

.- Computer Vision.

.- WeldViT: A Lightweight Network for Online Identification of Multi-Label Welding Defects.

.- Impact of Replay Ratios on Performance and Efficiency in Continual Learning for Skeleton-based Action Recognition.

.- Extending YOLO for Feature-Based Classification Through Numerical-to-Image Transformation.

.- Lost in the Noise: Evading and Detecting Backdoors in Conditional Diffusion Models.

. SkinPalNet: An Advanced Ensemble Model for Skin Cancer Diagnosis with Computer Vision Approach.

.- Enhancing Minimarket Customer Experience through YOLOv8-Powered Checkout Systems.

.- Brain Tumor MRI Interpretation: Towards a Benchmark for Medical Visual Question Answering.