Optimization, Learning Algorithms and Applications : 5th International Conference, OL2A 2025, Sesti Levante, Italy, April 28-30, 2025, Proceedings, Part II (Communications in Computer and Information Science)

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Optimization, Learning Algorithms and Applications : 5th International Conference, OL2A 2025, Sesti Levante, Italy, April 28-30, 2025, Proceedings, Part II (Communications in Computer and Information Science)

Pereira, Ana I. (EDT)/ Fernandes, Florbela P. (EDT)/ Coelho, João P. (EDT)

ウェブストア価格 ¥14,639（本体¥13,309）
Springer（2025/08発売）
外貨定価 US$ 64.99
ポイント 133pt

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製本 Paperback:紙装版/ペーパーバック版／ページ数 258 p.
言語 ENG
商品コード 9783032001399

Description

The two-volume set CCIS 2617 and 2618 constitutes the refereed post-conference proceedings of the 5th International Conference on Optimization, Learning Algorithms and Applications, OL2A 2025, held in Sesti Levante, Italy, during April 28 30, 2025.

The 38 revised full papers presented in these proceedings were carefully reviewed and selected from 92 submissions. The papers are organized in the following topical sections:

Part I: Optimization; Optimization in Control Systems Design; Artificial Intelligence in Healthcare and Medicine; and Deep Learning.

Part II: Optimization in the SDG context; Machine Learning; and Machine Learning and Artificial Intelligence in Robotics.

.- Optimization in the SDG context.
.- Application of Continuous and Periodic Review Models to Optimize Inventory Management in Dynamic Demand Scenarios.
.- Social Context in Fake News Diffusion.
.- Integrating Renewable Energy into Sustainability Metrics: a multicriteria decision.
.- A Secure Architecture for Supply-chain Orders Exchange between Textile and Clothing Companies.
.- Machine Learning.
.- Partial Knowledge Predictive Models for Hydrocarbon Storage.
.- Districting Methods for Water Distribution Network.
.- Enhancing Soil Organic Carbon Prediction: A Machine Learning Approach with Outlier Removal.
.- A Personalized Math Learning Experience with Clustering and Random Forest Algorithms.
.- Macroeconomics' Forecasting using Machine Learning Approaches by Policy Makers: A Case Study Analysis.
.- TI-FPCA: Effective and Interpretable Dimensionality Reduction with Transform-Invariant Functional Principal Component Analysis.
.- Prediction of Average Power Produced by Wind Turbines Using MLP Neural Networks.
.- OML-AD: Online Machine Learning for Anomaly Detection in Time Series Data.
.- Machine Learning and Artificial Intelligence in Robotics.
.- AI-Powered Tutoring for Personalized Learning.
.- Markerless Geometric Inspection Planning based on Greedy Algorithm with Registration Stability Constraint.
.- Comparing RL Policies for Robotic Pusher.
.- Reward-function design for Discrete and Continuous Mapless Navigation.
.- Object Classification using 2D-LiDAR and YOLO for Robot Navigation.