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IEEE CEC 2027: IEEE Congress on Evolutionary Computation

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截稿日期:
2027-02-28 还有 127 天
通知日期:
2027-04-07
会议日期:
2027-07-25
会议地点:
Edinburgh, UK
届数:
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CCF: C   ICORE: B   浏览: 135125   关注: 40   参加: 19
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IEEE CEC
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会伴指数 (CP-I)

52.6 / 100
全站第 1,170 名 / 共 5,759 个会议 · 前 21%

人工智能与机器学习 第 104 / 751

学术认可 (35%)
72
投稿选择性 (20%) 无数据 —— 按中性基准 50 分计入 —
会议传承 (20%)
19
社区关注 (10%)
54
资料公开度 (15%)
55

用到的输入: 收录等级：CCF C, ICORE B · 有据可查的届次：1 · 在会伴关注它的研究者：40 人 · 过去 24 个月打开过本页的研究者：11 人

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置信度 80% —— 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 2026-10-24

征稿

IEEE CEC 2027 (IEEE Congress on Evolutionary Computation) is a CCF C / ICORE B conference held in Edinburgh, UK on 2027-07-25. The paper submission deadline is 2027-02-28. Acceptance notifications are sent on 2027-04-07.

The IEEE Congress on Evolutionary Computation (IEEE CEC) is a world-class event in the field of Evolutionary Computation. One of the flagship conferences of the IEEE Computational Intelligence Society (IEEE CIS) and held annually since 1994, it provides a forum to bring together researchers and practitioners from all over the world to present and discuss their research findings on Evolutionary Computation. We invite original, previously unpublished contributions from researchers, practitioners and educators across the full breadth of evolutionary computation, from theoretical foundations to real-world applications. IEEE CEC 2027 will be held in Edinburgh, Scotland, a vibrant capital renowned for its world-leading universities and research community and, in late July, for the festivals that fill the city each summer. We warmly invite the community to join us for an outstanding scientific programme in an inspiring setting. ALGORITHMS Ant colony optimization and swarm intelligence Artificial immune systems Coevolutionary systems Coevolution Cultural algorithms Differential evolution Estimation of distribution algorithms Evolutionary computation theory Evolutionary developmental systems Evolutionary programming Evolution strategies Genetic algorithms Genetic programming Heuristics Interactive evolutionary computation Learning classifier systems Memetic algorithms Multi-meme and hybrid algorithms Molecular and quantum computing Multi-objective evolutionary algorithms Parallel and distributed algorithms Particle swarm optimization Representation and operators Self-adaptation in evolutionary computation MACHINE LEARNING FOR OPTIMIZATION & EVOLUTIONARY LEARNING Automated design of heuristics Evolutionary fuzzy systems Evolutionary neural architecture search Evolutionary reinforcement learning Fairness-aware optimization Federated and secure optimization Large language models for optimization Metaheuristics and hyper-heuristics Multi-objective machine learning Neural optimization Surrogate-assisted optimization Algorithm portfolios OPTIMIZATION Combinatorial Optimization Constraint handling Dynamic optimization Large-scale optimization Multi-modal optimization Multi-objective optimization Numerical optimization Optimization in the presence of uncertainty Robust optimization RELATED TOPICS Art and music Artificial life and adaptive behavior Autonomous mental and behavior development Biometrics Bioinformatics and computational biology Classification Clustering Data mining Defense and cybersecurity Drug design Embodied robotics Engineering design Evolutionary games and multi-agent systems Evolvable hardware Evolutionary software engineering Evolutionary robotics Finance and economics Intelligent systems applications Real-world applications AI ethics and governance THEORIES Causality and evolvability Convergence Fitness landscape analysis Robustness and neutrality Runtime analysis Scalability and complexity analysis
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