Coke Price Prediction Based on ELM Optimized by Double-elite Evolution Salp Swarm Algorithm

Coke is one of important industrial raw materials, and accurate prediction of its future price trend has great significance for making production scheduling plans of coking plants.Extreme learning machine（ELM） has strong generalization ability and fast computing speed, and it is suitable as the model of coke price prediction.However, the prediction performance of ELM is greatly affected by its key parameters, and its parameters need to be optimized.Based on this, a coke price prediction method is proposed by optimizing the key parameters of ELM using double-elite evolution salp swarm algorithm.Firstly, the double-elite evolutionary salp swarm algorithm（MDSSA） is proposed by introducing logistic chaotic mapping, improved convergence factor, adaptive inertia weights and double-elite evolutionary mechanism, so as to enhance the search capability of salp swarm algorithm（MDSSA）.Secondly, the connection weights and thresholds of ELM are optimized using MDSSA for finding the optimal parameters combination, so as to