Abstract
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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
A.E. Eiben, Z. Michalewicz, M. Schoenauer, J.E. Smith, Parameter control in evolutionary algorithms. IEEE Trans. Evol. Comput. 3, 124–141 (1999)
Y.J. Zheng, S.Y. Chen, Y. Lin, W.L. Wang, Bio-inspired optimization of sustainable energy systems: a review. Math. Probl. Eng. (2013)
X.S. Yang, Engineering Optimization: An Introduction with Metaheuristic Applications (Wiley, 2010)
M.S. Norlina, P. Mazidah, N.M. Sin, M. Rusop, Application of metaheuristic algorithms in nano-process parameter optimization, in 2015 IEEE Congress on Evolutionary Computation (CEC) (IEEE, 2015), pp. 2625–2630
N.M. Sabri, M. Puteh, M.R. Mahmood, An overview of gravitational search algorithm utilization in optimization problems, in 2013 IEEE 3rd International Conference on System Engineering and Technology (ICSET) (IEEE, 2013), pp. 61–66
P.J. Werbos, Computational intelligence for the smart grid-history, challenges, and opportunities. IEEE Comput. Intell. Mag. 6(3), 14–21 (2011)
R.J. Lin, Using fuzzy DEMATEL to evaluate the green supply chain management practices. J. Clean. Prod. 40, 32–39 (2013)
K. Shaw, R. Shankar, S.S. Yadav, L.S. Thakur, Supplier selection using fuzzy AHP and fuzzy multi-objective linear programming for developing low carbon supply chain. Expert Syst. Appl. 39(9), 8182–8192 (2012)
V. Jain, A.K. Sangaiah, S. Sakhuja et al., Supplier selection using fuzzy AHP and TOPSIS: a case study in the Indian automotive industry. Neural Comput. Appl. (2016). doi:10.1007/s00521-016-2533-z
O.W. Samuel, G.M. Asogbon, A.K. Sangaiah, P. Fang, G. Li, An integrated decision support system based on ANN and Fuzzy_AHP for heart failure risk prediction. Expert Syst. Appl. 68, 163–172 (2017)
A.K. Sangaiah, J. Gopal, A. Basu, P.R. Subramaniam, An integrated fuzzy DEMATEL, TOPSIS, and ELECTRE approach for evaluating knowledge transfer effectiveness with reference to GSD project outcome. Neural Comput. Appl. (2015). doi:10.1007/s00521-015-2040-7
G.H. Brundtland (ed.), Report of the World Commission on Environment and Development: Our Common Future, United Nations (1987), http://www.un-documents.net/wced-ocf.htm
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this chapter
Cite this chapter
Sangaiah, A.K., Abraham, A., Siarry, P., Sheng, M. (2017). Intelligent Decision Support Systems for Sustainable Computing. In: Sangaiah, A., Abraham, A., Siarry, P., Sheng, M. (eds) Intelligent Decision Support Systems for Sustainable Computing. Studies in Computational Intelligence, vol 705. Springer, Cham. https://doi.org/10.1007/978-3-319-53153-3_1
Download citation
DOI: https://doi.org/10.1007/978-3-319-53153-3_1
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-53152-6
Online ISBN: 978-3-319-53153-3
eBook Packages: EngineeringEngineering (R0)