International Journal of Intelligent Information Systems

Special Issue

Computational Intelligence in Data Science and Big Data: Theories and Applications

  • Submission Deadline: Jun. 30, 2015
  • Status: Submission Closed
  • Lead Guest Editor: Vijendra Singh
About This Special Issue
Data driven scientific discovery approach has already been agreed to be an important emerging paradigm for computing in areas including social, service, Internet of Things (or sensor networks), and cloud. Under this paradigm, Big Data is the core that drives new researches in many areas, from environmental to social. Special issue invites papers that report new research results that apply Computational Intelligence technologies, such as neural networks and learning algorithms, fuzzy systems, evolutionary computation, and other emerging techniques to Data Science and Big Data, ranging from theory, methodologies and algorithms for handling of big data, to their applications to the development of big data analytics systems.

This Special issue aims to promote new advances and research directions to address solicit experimental and theoretical works on data science and advanced analytics along with their application to real life situations. Topics of interest include (but are not limited to):

Theoretical Foundation

1. Computational intelligence, analytical modeling, simulation
2. Rough computing, fuzzy set, near set, soft set
3. Genetic algorithm, neural network, swarm intelligence
4. Big data science and foundations, analytics, visualization
5. Machine learning for big data
6. Hybridization intelligent techniques

Analytics, discovery and learning

1. Computational theories for big data analysis
2. Big data modeling and analytics
3. Big data visualization analytics
4. Web/online/network mining and learning
5. Data mining and data warehousing
6. Performance analysis, simulation, programming models
7. High performance data access toolkits and middleware
8. Programming models, abstractions for data-intensive computing
9. Data capturing, management and scheduling mechanisms
10. MapReduce, Hadoop and their applications
11. Distributed ensemble classifier
12. Mixed-type data analytics
13. Mixed-structure data analytics
14. Large scale optimization

Engineering Applications

1. Systems Engineering
2. Biological and Medical Sciences
3. Environmental Engineering
4. Telecommunication
5. Banking Sectors
6. Computational Finance
7. Wireless Sensor Networks
Lead Guest Editor
  • Vijendra Singh

    School of Engineering and Technology, NorthCap University, India, India

Guest Editors
  • Prudhvi Janga

    Department of Computer Science and Engineering, University of Cincinnati, Cincinnati, United States

  • Tejaswini Narayanan

    Electrical and Computer Engineering Department, University of California San Diego, La Jolla, United States

  • Lei Shi

    Intelligent Information department, Nagasaki Institute of Applied Science, Japan

  • Shuoben Bi

    School of Geograpy & Remote Sensing, Nanjing University of Information Science & Technology, Nanjing, China

  • Seema Jadhav

    Department of Instrumentation & Control Engineering, Pune University, Nashik, India

  • Vinay Shukla

    Department of Computer Science & Engineering, Institute of Technology & Management, Chehari Maharajganj, India

  • Khandoker Mohammed Mominul Haque

    Department of Computer Science and Engineering, Sylhet International University, Sylhet, Bangladesh

  • Seyyed Reza Khaze

    Elite Club, Dehdasht Branch, Islamic Azad University, Iran

  • Latifeh Pour Mohammad Bagher

    Department of Computer, Amirkabir University of Technology , Tehran, Iran