Cluster based Approach of Student’s Employment Prediction using PSO & EP
Keywords:
Job category prediction, cluster, PSO, EP, Self-adaptiveAbstract
In the present era of globalization where the geographical boundaries are no bar in terms of job opportunities, there is need of understanding and analyzing the students profile in terms of probable job offers. This work presents the cluster based concept in developing the easy and handy approach to define the possible job category for the engineering undergraduate students. The limitation of K-means has been explored in terms of their initialization and can’t consider in practice without re-verification. The optimal level of clustering has been developed using a hybrid approach of swarm intelligence and evolutionary computation. The dynamic approach of inertia weight in particle swarm optimization has been applied to provide the more suitable change with iteration while self-adaptive strategy in the evolutionary programming delivered the faster exploration. The proposed approach ensures the better balance between explorations vs. exploitation and delivered the optimal solution with high value of reliability.
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