Intelligent Automation and Soft Computing

Aims & Scope

An International Journal seeks to provide a common forum for the dissemination of accurate results about the world of intelligent automation, artificial intelligence, computer science, control, intelligent data science, modeling and systems engineering.

It is intended that the articles published in the journal will encompass both the short and the long term effects of soft computing and other related fields such as robotics, control, computer, vision, speech recognition, pattern recognition, data mining, big data, data analytics, machine intelligence, cyber security and deep learning.

It further hopes it will address the existing and emerging relationships between automation, systems engineering, system of systems engineering and soft computing.

The journal will publish original and survey papers on artificial intelligence, intelligent automation and computer engineering with an emphasis on current and potential applications of soft computing.

It will have a broad interest in all engineering disciplines, computer science, and related technological fields such as medicine, biology operations research, technology management, agriculture and information technology.

Metrics & Ranking

Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar

Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Computer Science and Mathematics, designed to support cutting-edge academic discovery.

Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• Generalization of Rough Sets using Modal Logics

  Citation: 373

  Authors: Y.Y., T.Y.

• Introducing Belbic: Brain Emotional Learning Based Intelligent Controller

  Citation: 269

  Authors: Caro, Danial, Nima

• Fusion-Based Supply Chain Collaboration Using Machine Learning Techniques

  Citation: 177

  Authors: Naeem, Taher, Alia, Sagheer, M., Haitham, Umar, Munir, Muhammad

• Modelling Supply Chain Information Collaboration Empowered with Machine Learning Technique

  Citation: 133

  Authors: Naeem, Alia, Leena, Taher, Sagheer, Muhammad, Haitham, Munir

• An Efficient Optimized Handover in Cognitive Radio Networks using Cooperative Spectrum Sensing

  Citation: 127

  Authors: H., K.

• Performances of K-Means Clustering Algorithm with Different Distance Metrics

  Citation: 119

  Authors: Taher, Muhammad, Raed, Afrozah, Mohammad, Munir, Muhammad, Muhammad

• Deformation Expression of Soft Tissue Based on BP Neural Network

  Citation: 113

  Authors: Xiaorui, Xun, Wei, Tong, Pengpai, Sunil

• Deep Learning-Based Skin Lesion Diagnosis Model Using Dermoscopic Images

  Citation: 83

  Authors: G., Chiai, Vinay, B.T., Gurram, Mohammad, S.

• An Intrusion Detection System for SDN Using Machine Learning

  Citation: 82

  Authors: G., S., T.

• Deep Neural Network Based Vehicle Detection and Classification of Aerial Images

  Citation: 81

  Authors: Sandeep, Arpit, Shilpa, Hammam, Sahar, Sami