In order to improve the performance of intensity modulation direct detection(IMDD) systems based on band-limited optoelectronic devices and direct modulation lasers(DML), solve the problem of high computational complexity of traditional equalizers, a simplified scheme for deep neural network(DNN) equalizers is proposed. Firstly, the adaptive momentum estimation (Adam) algorithm is used to update the weight coefficients of DNN, optimizing the iteration speed and convergence performance of traditional gradient descent algorithm. Then, based on this, discard layers and pruning operations are introduced to reduce the high computational complexity of DNN, reduce redundant connections in the network structure, and avoid overfitting phenomenon. Finally, the effectiveness and feasibility of the simplified scheme of DNN equalizer are verified in an 80 Gb/s bandlimited DML-IMDD simulation system.