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Review on Hybrid Swarm Algorithms for Feature Selection
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    Feature selection represents one of the critical processes in machine learning (ML). The fundamental aim of the problem of feature selection is to maintain performance accuracy while reducing the dimension of feature selection. Different approaches were created for classifying the datasets. In a range of optimization problems, swarming techniques produced better outcomes. At the same time, hybrid algorithms have gotten a lot of attention recently when it comes to solving optimization problems. As a result, this study provides a thorough assessment of the literature on feature selection problems using hybrid swarm algorithms that have been developed over time (2018-2021). Lastly, when compared with current feature selection procedures, the majority of hybrid algorithms enhance classification accuracy.

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Publication Date
Thu Jan 02 2020
Journal Name
Journal Of The College Of Languages (jcl)
The Kurdish experiment in the process of translation (1898-1991): ئةزمووني كوردي لة ثرؤسةي وةرطيَرِاندا (189 – 1991
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Translation as a human endeavor has occupied the attention of nations since it bridges the gab between cultures and helps in bringing out national integration. The translation of Kurdish literature started with personal efforts in which newspapers and magazines had played a vital role in supporting translation and paved the way for promoting the publication of Kurdish products.

      The bulk of the materials translated from Arabic exceeds that translated from other languages owing to the influence of religious and authoritarian factors.

The survey of the Kurdish journals was limited to the period 1898-1991 since it marked a radical and historic change represented by the birth of Kurdish journalis

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Publication Date
Sat Oct 01 2016
Journal Name
Journal Of Theoretical And Applied Information Technology
Factors affecting global virtual teams’ performance in software projects
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