Aggregation using Genetic Algorithms for FederatedLearning in Industrial Cyber-Physical Systems

Industry and academics are interested in indus-trial cyber-physical systems (ICPS). Complexity makes it hardto grasp these systems design and functioning. By offeringFedGA-ICPS, a federated learning framework based on geneticalgorithms, we can solve ICPS ́s performance and decision sup-port. To simulate the structure and behavior of these systems,we use ICPS. FedGA-ICPS investigates the performance of theICPS sensors by offering locally integrated learning models.Genetic algorithm then speeds up and improves federated learn-ing aggregation. Transfer learning is used to disseminate modelparameters across restricted entities. Fashion MNIST’s initiativeachieved notable outcomes