The invention provides a neural network equalization method used for an indoor visible light communication system, and belongs to the visible light wireless communication technology field. The method includes the steps: utilizing a ceiling bounce model to calculate a VLC channel impulse response, carrying out photoelectric conversion for a visible light power signal received by a receiving end, and sending a sequence to a neutral network channel equalizer after amplification sampling; utilizing a heredity algorithm to optimize initialization weights and thresholds among neurons, establishing a neural network for training, and minimizing an error function; and judging an output, restoring the sent sequence, and finally achieving an equalization purpose. According to the scheme, interference among codes is obvious minimized, an error rate is reduced, the communication quality is further improved, a transmission rate that the system can reach is increased, the training time is shortened, and the system complexity is reduced.