By Sudip Kumar Sahana, Sujan Kumar Saha
This quantity contains the complaints of the foreign convention on Computational Intelligence 2015 (ICCI15). This ebook goals to compile paintings from prime academicians, scientists, researchers and learn students from around the globe on all points of computational intelligence. The paintings consists more often than not of unique and unpublished result of conceptual, confident, empirical, experimental, or theoretical paintings in all components of computational intelligence. Specifically, the most important themes lined 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 internet analytics, robotics, computational neurosciences, neurodynamics, bioinspired and biomorphic algorithms, move disciplinary issues and purposes. The contents of this quantity may be of use to researchers and pros alike.
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Extra resources for Advances in Computational Intelligence: Proceedings of International Conference on Computational Intelligence 2015
3. 4. 5. 6. 7. 8. 9. Close Close Close Medium Medium Medium High High High Low Medium High Low Medium High Low Medium High Low high High Very high Rather medium Medium Low medium Very low Low Rather low Fig. 2 Input and Output for Fuzzy System Grid head chance calculation of each node of network is based on two fuzzy variables, and output is calculated based on the defuzziﬁcation method. 1 Input Variables Residual Energy: Residual energy is calculated as remaining energy of sensor nodes till current round.
Syst. 3(5), 522–530 (2010) 12. : 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.
7 Simulation diagram of fuzzy control method Fig. 8 Simulation result of P&O method Fig. D. Misra et al. Harmonics Minimization in Inverter Using Fuzzy Controller … Fig. 10 Simulation result of I&C Fig. 11 FFT analysis of I&C method Fig. D. Misra et al. Fig. 1 The Simulation has been Done on the Basis of Data as (a) In P&O method and incremental conductance method, R = 30 Ω, C = 500 μF, and L = 20 μH. The simulation result is shown in Fig. 8. In I&C method and incremental conductance method, R = 30 Ω, C = 500 μF, and L = 20 μH.