By Sudip Kumar Sahana, Sujan Kumar Saha
This quantity includes the complaints of the foreign convention on Computational Intelligence 2015 (ICCI15). This ebook goals to collect paintings from prime academicians, scientists, researchers and examine students from around the globe on all features of computational intelligence. The paintings consists quite often of unique and unpublished result of conceptual, confident, empirical, experimental, or theoretical paintings in all components of computational intelligence. Specifically, the foremost issues coated contain classical computational intelligence versions and synthetic intelligence, neural networks and deep studying, evolutionary swarm and particle algorithms, hybrid platforms optimization, constraint programming, human-machine interplay, computational intelligence for the net analytics, robotics, computational neurosciences, neurodynamics, bioinspired and biomorphic algorithms, go disciplinary subject matters and functions. The contents of this quantity may be of use to researchers and pros alike.
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Additional info for Advances in Computational Intelligence: Proceedings of International Conference on Computational Intelligence 2015
13(9), 924–935 (2002) 7. : Cluster head election techniques for coverage preservation in wireless sensor networks. Ad Hoc Netw. 5, 955–972 (2009) 8. : An energy efﬁcient cluster-head selection for wireless sensor networks. In: International Conference on Intelligent Systems, Modeling and Simulation, pp. 287–291 (2010) 9. : An efﬁcient approach for clustering in wireless sensor network using fuzzy logic. Int. Conf. Comput. Sci. Netw. Technol. (ICCSNT) 3, 1481–1486 (2011) 10. : An energy efﬁcient hierarchical clustering algorithm for wireless sensor networks.
In unequal clustering, clusters close to the sink are smaller in size to preserve energy for inter-cluster communication , and fuzzy logic has been used in WSN [9, 10] for resolving uncertainties in many scenarios. Therefore, in this paper, we propose an on-demand clustering with unequal cluster range for CHs. In the proposed approach, the CHs are selected based on their energy status and then assigned a cluster range using a fuzzy inference system (FIS). The cluster range of the proposed approach is a factor of nodes remaining energy, distance to sink and centrality to neighbor.
Ranking type-2 fuzzy numbers. IEEE Trans. Fuzzy Syst. 14(2), 287–294 (2006) 13. : Ranking of intuitionistic fuzzy numbers. In IEEE International Conference on Fuzzy Systems, 2008. FUZZ-IEEE 2008 (IEEE World Congress on Computational Intelligence), pp. 1971–1974. IEEE (2008) 14. : Multicriteria ranking of inventory replenishment policies in the presence of uncertainty in customer demand. Int. J. Prod. Econ. 71(1), 439–446 (2001) 15. : Classiﬁcation of inventory models and systems. Int. J. Prod.
Advances in Computational Intelligence: Proceedings of International Conference on Computational Intelligence 2015 by Sudip Kumar Sahana, Sujan Kumar Saha