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

控制論涉及描述我們日常生活中無處不在的系統之間的復雜交互和相互關系。機器學習發現系統中變量和變量集合之間的基本函數關系。機器學習和控制論學科的融合旨在通過從數據中學習的各種機制發現系統之間的各種交互形式。

《國際機器學習和控制論雜志》（IJMLC）專注于機器學習和控制論交匯處出現的關鍵研究問題，并作為快速傳播該領域最新進展的廣泛論壇。IJMLC 的重點是受工程、數學、認知科學和應用等不同學科啟發的機器學習和控制論方案的混合開發。與機器學習和控制論所有方面相關的新想法、設計方案、實現和案例研究都屬于 IJMLC 的范圍。

該期刊涵蓋的關鍵研究領域包括：

用于建模系統間交互的機器學習

用于支持發現系統-環境交互的模式識別技術

系統-環境交互的控制

生物和生物啟發系統中的生化相互作用

用于改進系統間通信方案的學習

International Journal Of Machine Learning And Cybernetics創刊于2010年，由Springer Berlin Heidelberg出版商出版，收稿方向涵蓋COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE全領域，此刊是中等級別的SCI期刊，所以過審相對來講不是特別難，但是該刊專業認可度不錯，仍然是一本值得選擇的SCI期刊 。平均審稿速度 ，影響因子指數3.1，該期刊近期沒有被列入國際期刊預警名單，廣大學者值得一試。