会议信息

IEAI 2027: International conference on Industrial Engineering and Artificial Intelligence

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截稿日期:
2026-11-30 还有 28 天
通知日期:
2026-12-30
会议日期:
2027-04-28
会议地点:
Seoul, South Korea
届数:
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会伴指数 (CP-I)

48.6 / 100
全站第 2,032 名 / 共 5,764 个会议 · 前 36%

人工智能与机器学习 第 217 / 752

学术认可 (35%) 无数据 —— 按中性基准 50 分计入 —
投稿选择性 (20%) 无数据 —— 按中性基准 50 分计入 —
会议传承 (20%)
59
社区关注 (10%)
10
资料公开度 (15%)
55

用到的输入: 有据可查的届次：8 · 过去 24 个月打开过本页的研究者：3 人

公开资料里还缺: 历年录用率 (+4.5) · 最佳论文记录 (+2.3)
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置信度 45% —— 分数中有多大比例来自实际观测到的数据，而不是中性基准。 这个分数是怎么算出来的 · 查看完整榜单 · 算法版本 1.2 · 算于 2026-11-01

征稿

IEAI 2027 (International conference on Industrial Engineering and Artificial Intelligence) is an academic conference held in Seoul, South Korea on 2027-04-28. The paper submission deadline is 2026-11-30. Acceptance notifications are sent on 2026-12-30.

The conference will bring together leading researchers, engineers and scientists in the domain of interest from around the world. Topics of interest for submission include, but are not limited to: 1. Applications of AI in Industrial Engineering Intelligent Manufacturing Systems AI-Driven Process Optimization Smart Factories and Industry 4.0 AI for Predictive Maintenance in Industrial Systems Robotics and Automation in Manufacturing AI in Supply Chain and Logistics Optimization Data-Driven Decision Making in Industrial Environments 2. Industrial Optimization and AI AI for Industrial Scheduling and Planning Multi-Objective Optimization using Machine Learning AI-Enhanced Process Control Systems Energy Efficiency Optimization in Manufacturing using AI AI-Enabled Simulation and Modeling for Industrial Systems 3. AI for Quality Control and Safety in Industry Machine Learning in Industrial Quality Control AI for Predicting Failures and Defects in Production Lines Safety Monitoring and Hazard Prevention in Industrial 4. Artificial Intelligence in Industrial Supply Chains AI and Blockchain Integration for Industrial Supply Chains Supply Chain Management with Deep Learning Techniques AI in Logistics and Transportation Networks Data Analytics for Improving Inventory Management in Industry AI for Risk Management and Resilience in Supply Chains 5. Smart Manufacturing and IoT IoT and AI Integration for Real-Time Industrial Monitoring AI in Predictive Maintenance using IoT Sensors Digital Twin Technology for Industrial Applications AI-Driven Decision Support Systems in Industrial Operations 6. Industrial Robotics and Autonomous Systems AI and Machine Learning in Industrial Robotics Autonomous Mobile Robots in Manufacturing Human-Robot Collaboration in Industrial Environments AI for Vision-Based Robotic Systems in Production Lines 7. AI in Industrial Process Automation Deep Learning for Process Automation in Industry Intelligent Automation Systems in Industrial Environments AI-Driven Adaptive Control Systems for Industrial Processes Edge AI for Real-Time Process Control and Decision Making 8. AI-Enabled Sustainability in Industrial Systems AI for Sustainable Manufacturing Practices Machine Learning for Energy Consumption Optimization Smart Waste Management and Recycling Systems using AI AI Solutions for Reducing Carbon Footprint in Industrial Operations 9. AI for Data-Driven Industrial Decision Making Predictive Analytics for Industrial Process Improvement AI in Industrial Big Data Analytics Decision Support Systems using AI in Industrial Operations Machine Learning for Process Optimization in Real-Time Manufacturing 10. AI in Industrial Human-Machine Interaction Human-Centered AI Design for Industrial Applications AI for Improving Human Performance in Industrial Systems Cognitive Computing and Human Factors in Industrial AI AI and Virtual Reality for Industrial Training and Simulation 11. AI and Industrial Cybersecurity AI for Threat Detection and Prevention in Industrial Networks Industrial Cybersecurity with Machine Learning AI-Driven Risk Management for Industrial IoT Autonomous Systems for Securing Critical Infrastructure in Industry 12. AI in Smart Energy and Industrial Systems AI for Smart Grid and Industrial Energy Management AI in Energy Optimization for Industrial Facilities Machine Learning for Predicting Energy Demand in Industrial Systems AI-Driven Energy Efficiency in Industrial Operations Other topics
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