Calls for papers


International Journal of Artificial Intelligence and Soft Computing
International Journal of Artificial Intelligence and Soft Computing


Special Issue on: "The Impact of Soft Computing Methods in Software Engineering and Big Data"

Guest Editors:
Jaime Lloret, Polytechnic University of Valencia, Spain
Ankit Chaudhary, Maharishi University of Management, USA
Deepti Mehrotra and Hari Mohan Pandey, Amity University, India

The artificial intelligence discipline is very broad, and within it can be found the wide and young research area of soft computing. Soft computing deals with the design of hybrid intelligent systems that, unlike hard computing techniques, are tolerant to imprecision, uncertainty, partial truth and approximation, and which can exploit this tolerance to achieve tractability, robustness and very low solution costs.

The main constituents of soft computing include fuzzy logic, neural computing, evolutionary computing, machine learning and probabilistic reasoning. More important than each of these constituents is the fact that they are complementary rather than competitive, being remarkable in the way that each contributes a distinct methodology for addressing problems in its domain.

In the last fifty years of artificial intelligence, the roles played by the various areas of soft computing have varied. Some of them, such as neural computing or machine learning, have been considered hot research topics since the very beginning, whereas research into fuzzy logic and fuzzy systems or into evolutionary computing (evolutionary strategy, genetic algorithms and genetic programming) became popular later. Others have experienced remarkable revivals, such as probabilistic reasoning with the appearance of belief or Bayesian networks during the late 1980s. Hence, soft computing has been highly dynamic area of research which has attracted the attention of many researchers. Today it is almost impossible to think about artificial intelligence without thinking about soft computing.

Soft computing and artificial intelligence are both used successfully in a variety of fields such as pattern recognition, computational biology, language learning, programming language design, data mining, software engineering (especially software language engineering), image processing, natural language processing, big data, cloud computing, and many more.

This special issue aims to provide a forum through which researchers can report recent advances and exchange knowledge in the field of soft computing in close relation to the state-of-the-art of software engineering, big data and other related areas.

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

  • Classification and regression methods
  • Unsupervised learning and clustering
  • Convex optimisation
  • Bayesian non-parametric models
  • Social network analysis
  • Feature selection
  • Anomaly detection
  • Engineering applications of big data analysis
  • Simulation optimisation
  • Data mining for energy saving and green production
  • Cognitive modelling
  • Computer-based engineering techniques
  • Software ergonomics
  • Data modelling techniques
  • Game theory
  • Application of object-oriented technology
  • Software engineering economics
  • Neural networks
  • Hybrid architectures
  • Rough sets
  • Granular computing
  • Automata theory
  • Multi-criteria decision making
  • Neural networks
  • Multi objects
  • Fuzzy set uncertainty
  • Knowledge acquisition
  • Knowledge representation
  • Evolutionary computation
  • Formal models
  • Quality management
  • Rational unified processing (RUP)
  • Intellectual property for software applications
  • Algebraic properties of automata and languages
  • History of software engineering
  • Systems engineering
  • Architecture of object-oriented systems
  • Relations of languages and automata to complexity theory
  • Soft computing techniques in health-oriented software
  • Soft computing and network architecture
  • Semi-supervised learning
  • Graph and link mining
  • Distributed optimisation
  • Matrix and tensor methods
  • Recommender systems
  • Online advertising
  • Fault diagnostics
  • Knowledge discovery from big data
  • Empirical studies of big data analytics and computational intelligence
  • Fuzzy logic and its applications
  • Software maintenance and evaluation
  • Knowledge engineering methods and practices
  • Software engineering professionalism
  • Impact of CASE on software development lifecycle
  • Software engineering methods and practices
  • Artificial intelligence
  • Software security analysis
  • Software engineering demographics
  • Software design and its applications
  • Software deployment
  • UML
  • Grammars and automata
  • Test-driven development
  • Turing machine
  • Modelling languages
  • Object-oriented systems
  • Parallel software architecture
  • Network software architecture
  • Cloud computing software architecture
  • Algorithm design
  • Estimations of parameters of codes
  • Petri net languages
  • Applications of formal languages
  • Project management
  • Software-defined networking (SDN)
  • Agile methods
  • Ambiguity in software development
  • Cellular automata and their applications
  • Soft computing in image processing
  • Soft computing and wireless network architecture and optimisation

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: 30 April, 2015

Notification to authors: 20 July, 2015

Final versions due by: 30 October, 2015