We propose a mean-field optimal control problem for the parameter identification of given pattern. The cost functional is based on Wasserstein distance between probability measures modeled and desired patterns. first-order optimality conditions corresponding to are derived using Lagrangian approach level. Based these we gradient descent method identify relevant parameters such as angle rotation...