Employee performance evaluation method based on improved deep dynamic fuzzy neural network

The invention discloses an employee performance evaluation method based on an improved deep dynamic fuzzy neural network, and relates to the technical field of employee performance evaluation, and the method comprises the following steps: S1, constructing a DFNN model which comprises five layers: an input layer, a membership function layer, a T-norm layer, a normalization layer and an output layer, and is used for making a membership function rule to train data, meanwhile, the learning speed is increased by using a hierarchical learning mode; according to the employee performance evaluation method based on the improved deep dynamic fuzzy neural network, through a PSO-DFNN algorithm, aiming at the defects of a DFNN algorithm, a dynamic and deep structure is added to increase the data training ability of a model, meanwhile, a membership function is improved, and parameters are optimized by adopting the PSO algorithm, so that the optimal training effect is achieved; and meanwhile, the result of the method is mor