Intelligent Data Analysis provides a forum for the examination of issues related to the research and applications of Artificial Intelligence techniques in data analysis across a variety of disciplines. These techniques include (but are not limited to): all areas of data visualization, data pre-processing (fusion, editing, transformation, filtering, sampling), data engineering, database mining techniques, tools and applications, use of domain knowledge in data analysis, big data applications, evolutionary algorithms, machine learning, neural nets, fuzzy logic, statistical pattern recognition, knowledge filtering, and post-processing.

In particular, papers are preferred that discuss development of new AI related data analysis architectures, methodologies, and techniques and their applications to various domains.

Papers published in this journal are geared heavily towards applications, with an anticipated split of 70% of the papers published being applications-oriented, research and the remaining 30% containing more theoretical research. Manuscripts should be submitted in *.pdf format only. Please prepare your manuscripts in single space, and include figures and tables in the body of the text where they are referred to.