A NEW NATURE INSPIRED OPTIMIZATION TECHNIQUE

Background: In this era, the nature inspired Algorithms have become major domain that is used for the optimization because of their derivative free existence and ability to escape the local dilemma of optima. In the software reliability parameters estimation, these algorithms have played a very important role. Objective: in this paper, it proposes the new nature-based algorithm, which is inspired by the smooth coated otter hunting capacity for software reliability parameter optimization models. The most striking characteristic of the otters is party hunting. This essay explores Otter's intelligent hunting behavior to optimize machine stability models. Method: Otters collaborate closely and demonstrate outstanding coordination. Smarter fish hunting potential of smooth coated otters separates them from other algorithms focused on swarm intelligence. Three phases of otter shooting, which primarily move in V formations to move the prey, enter the river and strike the prey on the shore aggressively, are done. The suitability of the proposed algorithm is shown by three machine reliability models. Result: The assessment reveals that the proposed algorithms have a lower SSE and lower MSE value by 75% and 50% over ABC, GA and PSO. Conclusion: For the parameter estimation of software reliability models Smooth coated otter foraging behavior provides an important role. The results are encouraging the researchers to keep the research further in this field. Other optimizing issues with smooth coated otters can be added.