Stress Diagnosis among Academic Fraternity using Bird-Based Soft Computing Techniques

Abstract: Stress is a severe psychological disorder that has a significant impact on psychological and physiological behavior of academic fraternity. To evaluate the rate of educational stress among students and teachers, a dataset of academic fraternity is collected and examined. To discover an optimal set of characteristics for a bi-objective stress diagnosis problem, three different bird-based swarm Intelligence (SI) metaheuristic algorithms namely Crow search algorithm (CSA), Emperor penguin optimizer (EPO), and Harris hawk Optimization (HHO) has been explored. The performance of these methods in discovering optimal set of features required for stress diagnosis among academic fraternity has been explained.

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