Intelligent decision support systems for sustainable computing

Arun Kumar Sangaiah*, Ajith Abraham, Patrick Siarry, Michael Sheng

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

2 Citations (Scopus)


In sustainable computing, Intelligent Decision Support Systems (IDSS) has been adopted for prediction, optimization and decision making challenges under variable number constraints based on un-structured data. The traditional systems are lack of efficiency, limited computational ability, inadequate and impreciseness nature of handling sustainable problems. Despite, Computational Intelligence (CI) paradigms have used for high computational power of intelligence system to integrate, analyze and share large volume of un-structured data in a real time, using diverse analytical techniques to discover sustainable information suitable for better decision making. In addition, CI has the ability to handle complex data using sophisticated mathematical models, analytical techniques. This chapter provides a brief overview of computational intelligence (CI) paradigms and its noteworthy character in intelligent decision support and analytics of sustainable computing problems. The objective of this chapter is to study and analyze the effect of CI for overall advancement of emerging sustainable computing technologies.

Original languageEnglish
Title of host publicationIntelligent decision support systems for sustainable computing
Subtitle of host publicationparadigms and applications
EditorsArun Kumar Sangaiah, Ajith Abraham, Patrick Siarry, Michael Sheng
Place of PublicationCham
PublisherSpringer, Springer Nature
Number of pages6
ISBN (Electronic)9783319531533
ISBN (Print)9783319531526
Publication statusPublished - 2017

Publication series

NameStudies in Computational Intelligence
ISSN (Print)1860-949X


  • Computational intelligence
  • Intelligent decision support systems
  • Sustainable computing


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