Memetic Computing
| 短名 | Memetic Comp. |
| Journal Impact | 3.44 |
| 国际分区 | OPERATIONS RESEARCH & MANAGEMENT SCIENCE(Q2) |
| 期刊索引 | SCI Q2中科院 2 区 |
| ISSN | 1865-9284, 1865-9292 |
| h-index | 40 |
| 国内分区 | 计算机科学(2区)计算机科学计算机人工智能(2区)计算机科学运筹学与管理科学(2区) |
模因被定义为存在于大脑中并通过模仿过程在人群中传播的可转移信息的基本单位。从算法的角度来看，模因已被视为先验知识的构建块，以任意计算表示（例如，局部搜索启发式、模糊规则、神经模型等）表示，这些表示是通过以下人员的经验获得的人或机器，并且可以在各种问题中被模仿（即重用）。模因计算杂志欢迎将上述模因的社会文化概念纳入人工系统的论文，特别强调提高计算和人工智能技术的功效通过明确的先验知识整合进行搜索、优化和机器学习。因此，该杂志的目标是成为对混合、知识驱动的计算方法进行高质量理论和应用研究的渠道，这些方法可能具有以下任一类别的模因特征：类型 1：与人类集成的通用算法精心设计的启发式方法可以捕获某种形式的先验领域知识；例如，传统的模因算法将进化全局搜索与特定问题的局部搜索混合在一起。类型 2：能够从各种可用选择中自动选择、调整和重用最合适的启发式算法的算法；例如，在给定手头优化问题的情况下，学习全局搜索算子和多个局部搜索方案之间的映射。类型 3：根据经验自主学习的算法，自适应地重用从相关问题中提取的数据和/或机器学习模型作为新的先验知识感兴趣的目标任务；示例包括但不限于迁移学习和优化、多任务学习和优化，或任何其他多 X 进化学习和优化方法。
期刊主页投稿网址| 涉及主题 | 计算机科学人工智能数学机器学习数学优化算法社会学社会科学复杂系统工程类生物经济程序设计语言哲学进化算法物理操作系统遗传算法地理心理学统计局部搜索（优化）认识论地质学 |
| 出版信息 | 出版商: Springer Verlag，出版周期: 4 issues per year，期刊类型: journal |
| 基本数据 | 创刊年份: 2009，原创研究文献占比: 100.00%，自引率:12.10%， Gold OA占比: 8.64% |
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