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Titlebook: Computational Intelligence in Data Mining; Proceedings of the I Himansu Sekhar Behera,Durga Prasad Mohapatra Conference proceedings 2017 Sp

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51#
發(fā)表于 2025-3-30 09:16:03 | 只看該作者
https://doi.org/10.1007/978-3-031-54837-6o emulate the data received from supplier ground system which in turn will be receiving ACARS from flying fleet in real time. This is a User-friendly application which has a very powerful impact on aerospace division by eliminating the uncertain economic loss.
52#
發(fā)表于 2025-3-30 12:59:35 | 只看該作者
53#
發(fā)表于 2025-3-30 20:17:51 | 只看該作者
54#
發(fā)表于 2025-3-31 00:07:45 | 只看該作者
Key Author Analysis in 1 and 1.5 Degree Egocentric Collaboration Network,he scientific efficacy of an individual. Finally, compare the results of all those types of network and found that the 1.5 degree egocentric networks are useful to appraise the performance of researchers.
55#
發(fā)表于 2025-3-31 03:18:30 | 只看該作者
56#
發(fā)表于 2025-3-31 09:04:36 | 只看該作者
57#
發(fā)表于 2025-3-31 12:09:45 | 只看該作者
Public Governance in Member States,ary approaches with the output images got using HE and HS. We report that evolutionary methods result in better contrast enhancement than classical methods in all our test cases. ABC approach outperformed GA approach, when output images were subjected to quantitative comparison.
58#
發(fā)表于 2025-3-31 13:29:25 | 只看該作者
https://doi.org/10.1007/978-3-8350-5406-6 are compared with some other benchmark approaches. Simulation results divulge that the proposed approach can be efficiently used for solving clustering problems as it avoids the trapping in local optima and helpful for faster convergence.
59#
發(fā)表于 2025-3-31 18:12:53 | 只看該作者
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