Random Replacement Crisscross Butterfly Optimization Algorithm for Standard Evaluation of Overseas Chinese Associations

The butterfly optimization algorithm (BOA) is a swarm intelligence proposed in 2019 that simulates the foraging behavior of butterflies. Similarly, BOA itself has certain shortcomings, such as slow convergence speed and low solution accuracy. To cope with these problems, two strategies are introduced to improve performance BOA. One random replacement strategy, which involves replacing position current optimal used increase speed. other crisscross search utilized trade off capability exploration exploitation remove local dilemmas whenever possible. In this case, we propose novel optimizer named (RCCBOA). order evaluate RCCBOA, comparative experiments conducted another nine advanced algorithms on IEEE CEC2014 function test set. Furthermore, RCCBOA combined support vector machine (SVM) feature selection (FS)—namely, RCCBOA-SVM-FS—to attain standardized construction model overseas Chinese associations. It found reasonableness bylaws; regularity general meetings; right elect, be elected, vote importance planning standardization Compared learning methods, RCCBOA-SVM-FS an up 95% accuracy when dealing normative prediction problem Therefore, constructed helpful for guiding orderly healthy development