An Optimization Method for the Addition Quantity of Ferroalloys Based on FNN and Improved Particle Swarm Algorithm

Aiming at the problem that the addition quantity of ferroalloys is difficult to determine in the industrial production process, this paper proposes an optimization method for the addition quantity of ferroalloys based on FNN and an improved particle swarm algorithm. First, the model uses an FNN network to design a generated element soft sensing model, obtaining an accurate mathematical description of the alloy addition quantity problem. Then, an improved multi-objective particle swarm optimization algorithm is applied to solve the ferroalloy addition quantity, thereby reducing the production cost of ferroalloys. Finally, a decision solution selection strategy prioritizing steel quality is used to derive the optimal ferroalloy addition quantity information. The simulation results show that the proposed method can determine the ferroalloy addition quantity under the constraints of minimum cost and minimum error, verifying the effectiveness and rationality of the model.