Artificial and Computation Research Society introduces the publication of the international Journal of Artificial and Computational Intelligence (IJACOI).

This journal is based on the continuous model in English and adopts the open-access model, meaning that all interested readers have free access to the journal's homepage and articles without the need for subscription. Users are allowed to read, download, copy, distribute, print, search, or link to the full texts of the articles in this journal without asking prior permission from the publisher or the author.

All published papers of IJMLTA will be submitted to Google Scholar for indexing.

IJMLTA is a high-quality peer-reviewed journal, in which every article will be peer-reviewed by several experts in the relevant field and assigned unique DOIs by CrossRef. Upon acceptance, articles will be published in the latest open volume. One continuous volume per year is published.

JFFHMT welcomes only original research and review papers that focus on Machine Learning Techniques and Applications. While these topics are far reaching and interdisciplinary in nature, IJMLTA is dedicated to cultivating a cohesive and consistent journal that both reflects its core themes and looks forward to new and innovative applications. With this in consideration, please review the following paper topics as a general guide for the types of articles that are applicable to the interests of IJMLTA readers:

	Track -1 Machine Learning Techniques	Track -2 Applications
	• Linear Regression • Logistic Regression • Decision Tree • Support Vector Machine • Naive Bayes • K-Nearest Neighbour • Random Forest • Dimentionality Reduction Algorithms • Gradient Boosting Algorithms • Self Organizing Maps • Multivariate adaptive regression • Neural Networks • Hidden Markov Model • Gaussian Mixture • Discriminant Analysis • Fuzzy C-means • K-Medoids