Magnetorheological (MR) foam is a magnetic polymer composite (MPC) that can be used for soft sensors and actuators in soft robotics. Modeling mechanical properties and magnetostriction behavior of MR foam is critical to developing into MR foam devices. This study uses extreme learning machines (ELM) and artificial neural networks (ANN) to predict magnetostriction behavior.These models describe the nonlinear relationship between different carbonyl iron particle compositions, magnetic field, strain, and normal force. The model's hyperparameters (learning algorithms and activation functions) are varied. For ANN, RMSProp, and ADAM learning algorithms were used with

No abstract