International Journal Of Machine Learning And Cybernetics

Journal Title：International Journal Of Machine Learning And Cybernetics

Cybernetics is concerned with describing complex interactions and interrelationships between systems which are omnipresent in our daily life. Machine Learning discovers fundamental functional relationships between variables and ensembles of variables in systems. The merging of the disciplines of Machine Learning and Cybernetics is aimed at the discovery of various forms of interaction between systems through diverse mechanisms of learning from data.

The International Journal of Machine Learning and Cybernetics (IJMLC) focuses on the key research problems emerging at the junction of machine learning and cybernetics and serves as a broad forum for rapid dissemination of the latest advancements in the area. The emphasis of IJMLC is on the hybrid development of machine learning and cybernetics schemes inspired by different contributing disciplines such as engineering, mathematics, cognitive sciences, and applications. New ideas, design alternatives, implementations and case studies pertaining to all the aspects of machine learning and cybernetics fall within the scope of the IJMLC.

Key research areas to be covered by the journal include:

Machine Learning for modeling interactions between systems

Pattern Recognition technology to support discovery of system-environment interaction

Control of system-environment interactions

Biochemical interaction in biological and biologically-inspired systems

Learning for improvement of communication schemes between systems

控制论涉及描述我们日常生活中无处不在的系统之间的复杂交互和相互关系。机器学习发现系统中变量和变量集合之间的基本函数关系。机器学习和控制论学科的融合旨在通过从数据中学习的各种机制发现系统之间的各种交互形式。

《国际机器学习和控制论杂志》（IJMLC）专注于机器学习和控制论交汇处出现的关键研究问题，并作为快速传播该领域最新进展的广泛论坛。IJMLC 的重点是受工程、数学、认知科学和应用等不同学科启发的机器学习和控制论方案的混合开发。与机器学习和控制论所有方面相关的新想法、设计方案、实现和案例研究都属于 IJMLC 的范围。

该期刊涵盖的关键研究领域包括：

用于建模系统间交互的机器学习

用于支持发现系统-环境交互的模式识别技术

系统-环境交互的控制

生物和生物启发系统中的生化相互作用

用于改进系统间通信方案的学习

International Journal Of Machine Learning And Cybernetics创刊于2010年，由Springer Berlin Heidelberg出版商出版，收稿方向涵盖COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE全领域，此刊是中等级别的SCI期刊，所以过审相对来讲不是特别难，但是该刊专业认可度不错，仍然是一本值得选择的SCI期刊 。平均审稿速度 ，影响因子指数3.1，该期刊近期没有被列入国际期刊预警名单，广大学者值得一试。