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AAIEE 2025: IEEE International Symposium on the Application of Artificial Intelligence in Electrical Engineering

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截稿日期:
2024-12-05
通知日期:
2025-01-05
会议日期:
2025-04-25
会议地点:
Beijing, China
浏览: 8491   关注: 1   参加: 0

会伴指数 (CP-I)

44.2 / 100
全站第 3,107 名 / 共 5,682 个会议 · 前 55%

电气与电子工程 第 239 / 509 人工智能与机器学习 第 367 / 739

证据有限：这个会议不在 CCF / ICORE / QUALIS 任何一份榜单里，也没有录用率数据，因此分数的大部分回落到了中性基准。
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%) 无数据 —— 按中性基准 50 分计入 —
社区关注 (10%)
15
资料公开度 (15%)
35

用到的输入: 在会伴关注它的研究者：1 人 · 过去 24 个月打开过本页的研究者：2 人

公开资料里还缺: 历年录用率 (+4.5) · 历届信息 (+3.0) · 最佳论文记录 (+2.3)
主办方认领本会议后，可直接在这一页补上；分数每晚重算。如何提升这个分数

置信度 25% —— 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 1.1 · 算于 2026-09-17

征稿

AAIEE 2025 (IEEE International Symposium on the Application of Artificial Intelligence in Electrical Engineering) is an academic conference held in Beijing, China on 2025-04-25. The paper submission deadline is 2024-12-05. Acceptance notifications are sent on 2025-01-05.

We invite submissions of original research papers on the topics related to application of artificial intelligence in electrical engineering for the upcoming AAIEE conference. The conference aims to provide a platform for researchers, engineers, and practitioners from academia, industry, and government to exchange ideas, share experiences, and present their latest research findings in these fields. Topics for submission include, but are not limited to: Track 1: Artificial Intelligence in Power Systems AI-based power system intelligent planning Probabilistic load modeling for power system expansion planning Deep learning for power system data analysis Optimal operation of power systems with large-scale new energy sources taking into account weather factors Economic dispatch of power systems with large-scale new energy sources taking into account weather factors Analysis of power system automation control strategy based on intelligent technology Cybersecurity in Artificial Intelligence-based power systems Use machine learning for load prediction Predictive maintenance of power system components Artificial intelligence for distributed energy management Track 2: Artificial Intelligence in Clean Energy Power Generation Probabilistic photovoltaic generation forecasting Probabilistic modeling of photovoltaic systems Planning of photovoltaic power generation Uncertainty quantification and scenario generation of photovoltaic Applications of reinforcement learning in energy systems Optimization and machine learning in energy harvesting system Research on high-accuracy and high-resolution numerical weather prediction and forecasting for power production needs Power load forecasting under typical and atypical weather types Probabilistic tidal wave analysis for power systems with wind farms considering weather factors Research on the simulation method of new energy generation scenario based on statistical machine learning Track 3: Artificial Intelligence in High Voltage and Insulation Technology Predictive modeling of insulation degradation Evaluation of the main insulation condition of the generator Optimize insulation design Automatic high voltage substation Secondary insulation monitoring system of voltage transformer based on artificial intelligence technology Research on path planning method of transmission line combined with artificial intelligence technology Research on coordinated planning method of transmission network and distribution network in large cities Track 4: Artificial Intelligence Technology Assists in the Construction of Digital Power Grids Machine learning in agriculture and rural microgrid Assessment of available transmission capacity of new energy grid-connected power generation systems taking into account weather factors Solutions for smart grid interoperability Power theft detection Smart home energy management system Integration of iot and smart grid Uav intelligent inspection Intelligent fault diagnosis of unit based on neural network The output power of the unit is forecasted in the short and medium term Track 5: Intelligent Grid Operation and Maintenance Monitoring Based on Artificial Intelligence Grid reliability analysis and early warning considering catastrophic weather factors Real-time monitoring of power grid operation status Energy flow optimization and control Predictive maintenance of power grid equipment Fault detection and response based on artificial intelligence Self-healing technology in smart grid Application of remote sensing and artificial intelligence in power grid inspection Analysis of power grid operation and maintenance data based on machine learning Track 6: Artificial Intelligence in the Electricity Market Electricity market price forecast and trend analysis Power demand forecasting and load management based on artificial intelligence Electricity market trading strategy optimization Electricity market risk assessment and management Transaction credit management based on artificial intelligence facial recognition technology Electricity market simulation and modeling Dynamic pricing model of electricity market
由 Dou Sun 最后更新于

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相关期刊

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CKnowledge-Based Systems7.2Elsevier0950-7051
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