Medical Pattern Matching Using Constrained Squirrel Search Algorithm

Abstract

Medical pattern matching plays an essential role in our daily life, as each individual depends on that in a number of the other aspects. To realize higher and economical results the method itself is carried out in multiple phases. The pattern matrixes that hold the relation between the variables and therefore the factors that are generated by the Squirrel Search formula are studied and appropriate techniques are utilized for pattern recognition. This paper concludes with results and discussions of the optimisation algorithms, at the side of a artistic movement scope of the formula within the medical pattern recognition and matching. This paper also proposes an enhancement of the Squirrel search algorithm (SSA)[5] by extending it for constrained optimization problems. This Squirrel search algorithm is initially benchmarked on a group of test issues together with CEC2014 [7] to check and verify its performance. SSA works by imitating the dynamic search behavior of southern flying squirrels as well as their effective locomotion method called gliding. Although the prevailing Squirrel Search formula has proven to be a lot of correct and per exceptional convergence behaviour compared with the opposite reported optimizers, the formula isn't yet enforced for resolution affected consistent with issues. this will be achieved by introducing constraints and call variables to the prevailing formula and validation of a similar with a selected set of affected benchmark functions.