“…11 To overcome these shortcomings, some optimization algorithms are usually used to optimize the parameters of neural network, such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), Grey Wolf Optimizer (GWO), and so on. [12][13][14][15][16] At present, the use of hybrid algorithms has become the choice of more scholars, such as Grey Wolf Optimizer-Long Short-Term Memory (GWO-LSTM), Multi-Objective-Particle Swarm Optimization-Grey Relation Analysis (MOPSO-GRA), Multi-Objective-Particle Swarm Optimization-Radial Basis Function based Support Vector Regression (MOPSO-RBFSVR), GA-ANN, Continuous Genetic Algorithm-Particle Swarm Optimization (CGA-PSO), etc.…”