Advances in Computational Intelligence: Proceedings of by Sudip Kumar Sahana, Sujan Kumar Saha

By Sudip Kumar Sahana, Sujan Kumar Saha

This quantity includes the complaints of the overseas convention on Computational Intelligence 2015 (ICCI15). This e-book goals to collect paintings from major academicians, scientists, researchers and learn students from around the globe on all points of computational intelligence. The paintings consists mostly of unique and unpublished result of conceptual, positive, empirical, experimental, or theoretical paintings in all parts of computational intelligence. Specifically, the foremost issues lined contain classical computational intelligence versions and synthetic intelligence, neural networks and deep studying, evolutionary swarm and particle algorithms, hybrid structures optimization, constraint programming, human-machine interplay, computational intelligence for the net analytics, robotics, computational neurosciences, neurodynamics, bioinspired and biomorphic algorithms, pass disciplinary subject matters and functions. The contents of this quantity should be of use to researchers and execs alike. 

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Inf. Control 8, 338–353 (1965) 4. : Cluster head selection protocol using fuzzy logic for wireless sensor networks. Int. J. Comput. Appl. 97, 38–43 (2014) 5. : A survey on routing protocols for wireless sensor networks. Ad Hoc Netw. 3(3), 325–349 (2005) 6. : Data gathering algorithms in sensor networks using energy metrics. IEEE Trans. Parall. Distrib. Syst. 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.

Table 2 contains the simulation parameters. 0013 pJ/bit/m4 Fig. 6 Number of alive nodes in GAPFL versus LEACH A Grid-Based Approach to Prolong Lifetime of WSNs … 21 Fig. 1 Simulation Results MATLAB [17] tool is used to get the simulation results, as shown in Figs. 6 and 7. GAPFL protocol prolongs WSNs lifetime in terms on number of rounds. We simulated and compare GAPFL with LEACH in various number of rounds. Simulation result is shown below. The above graph represents number of alive nodes in LEACH.

Prod. Econ. 34(2), 209–222 (1994) 16. : Survey on fuzzy multi-criteria decision-making approach. Control Decis. 23, 601–606 (2008) 54 M. Deb and P. Kaur 17. : Survey on intuitionistic fuzzy multi-attribute decision making approach. Control Decis. 25(11), 1601–1606 (2010) 18. : Intuitionistic fuzzy multiattribute decision making: an interactive method. IEEE Trans. Fuzzy Syst. 20(3), 514–525 (2012) 19. : Fuzzy sets. Inf. Control 8, 338–353 (1965) 20. : A compromise ratio ranking method of triangular intuitionistic fuzzy numbers and its application to MADM problems.

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