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Soft-computing modeling and pbkp_rediction of gender equality

Abstract:

ITC and E-government platforms are crucial to gather and mining data in order to develop strategies to ensure gender equality. We propose multiple methods from soft-computing to perform an analysis over gender equality data. A database of the evolution of anti-discrimination laws and gender equality regulations for 50 years (1960-2010), is codified to match a three-state neural network. The performance of the network is checked for such patterns. Clustering analysis is performed to group countries with similar behavior around the world. Finally, the evolution of gender equality laws worldwide is described and pbkp_redicted using exponential smoothing. The results show that in gender evolution, equality is far from being reached, especially in North Africa which continue with significant regulatory deficiencies. Otherwise changes (mostly for better)are to be expected, mainly in South America.