Calls for papers


International Journal of Mathematical Modelling and Numerical Optimisation
International Journal of Mathematical Modelling and Numerical Optimisation


Special Issue on: "Data Analytics and Modelling"

Guest Editor:
Prof. Srikanta Patnaik and Dr. Jyoti Ranjan Nayak, SOA University, India

The amounts of global data in all spheres have been increasing rapidly day by day. Organisations capture tera-bytes of information about their customers, suppliers and operations daily. Furthermore, millions of networked sensors embedded in the physical world and devices such as mobile phones and automobiles generate huge amounts of data through sensing, creating and communicating between each other. Multimedia sources and individuals with smart phones and on social network sites also contribute to fuelling this exponential growth.

This large pool of data, coined as “big data”, can be captured, communicated, aggregated, stored and analysed, and is now part of every sector and function of the global economy. Like other essential factors of production such as physical assets and human capital, it is becoming an increasingly important factor in modern economic activity, innovation and growth.

The objective of this special issue is to provide an opportunity for researchers working in the area of theory and applications of data sciences. The issue invites contributions from the academic community and industry experts, in order to present recent advances in this area.

Subject Coverage
Suitable topics include, but are not limited to, the following:

  • Classification
  • Regression
  • Cluster analysis
  • Time series analysis
  • Simulation
  • Data mining
  • Ensemble learning
  • Machine learning
  • Natural language processing
  • Neural networks
  • Supervised learning
  • Network analysis
  • Data fusion and data integration
  • Association rule learning
  • Crowd sourcing
  • Optimisation
  • Pattern recognition
  • Predictive modelling
  • Sentiment analysis
  • Signal processing
  • Spatial analysis
  • Statistics
  • Techniques for big data analysis
  • Unsupervised learning
  • Visualisation

Notes for Prospective Authors

Submitted papers should not have been previously published nor be currently under consideration for publication elsewhere. (N.B. Conference papers may only be submitted if the paper has been completely re-written and if appropriate written permissions have been obtained from any copyright holders of the original paper).

All papers are refereed through a peer review process.

All papers must be submitted online. To submit a paper, please read our Submitting articles page.

Important Dates

Manuscripts due by: 31 March, 2016

Notification to authors: 31 May, 2016

Final versions due by: 31 July, 2016