HYBRID PARTICLE SWARM OPTIMIZATION AND GENETIC ALGORITHM FOR MULTI-UAV FORMATION RECONFIGURATION
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Abstract
E-Learning is content and instructional methods delivered on a computer (whether on CDROM, the Internet, or an intranet), and designed to build knowledge and skills related to individual or organizational goals. Like any learning process, e-learning depends on effective communication of human knowledge, whether this occurs in a face-to-face classroom or across the Internet. The existing e-learning site just contains the learning contents and information. It does not have any recommendation of web pages of the website to reduce search space and to provide users the required and expected contents with optimized time. Our e-learning system tracks user sessions to get user log for optimizing search space and to generate population. Although a number of nature inspired algorithms exist in literature to solve optimization problems, yet there is always a need of new algorithm which can search for optimum solution in minimum time. This paper proposes a new optimization algorithm for solving optimization problem like search space optimization in a website. The proposed optimization algorithm has two functions namely current fitness and environmental fitness for optimization with improved accuracy.
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