In order to improve the convergence speed and the ability to jump out of the local optimal optimization algo-rithm,an improved sand cat algorithm fused with osprey mutation was proposed.First,the Bernoulli map is used to initial-ize the race value to prevent falling into the local optimal solution.Secondly,in order to increase the diversity of SCSO populations and the ability to jump out of the local optimum,the adaptive Gaussian Cauchy mixed mutation perturbation and osprey optimization algorithm were introduced,and the elite reverse learning mechanism was used to try to explore the reverse solution to accelerate the convergence speed.Finally,eight benchmark functions are tested and compared with the SCSO algorithm and the OOA algorithm,and the results show that the improved SCSO algorithm has the advantages of the two algorithms and the convergence speed is faster,It is applied to PV power prediction to further verify its effective-ness.
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