Abstract: The electrochemical method is proved to be an effective method to remove ammonia. However, the research on the energy consumption control is neglected. This paper uses artificial intelligence and back propagation neural network (BPNN) to establish the ammonia removal rate prediction model and intelligent control strategy. The model consists of a prediction module and a control module with BPNN algorithm model. Firstly, four hidden layers (per 60 neurons) and a negative feedback adjustment mechanism are used to develop the BPNN algorithm, optimize the model and predict the ammonia removal rate. Through parameter analysis and comparison of response surface models, the BPNN model proposed in this paper has better coefficient of determination and lower mean square error. According to the water quality changes and the determined target of ammonia removal rate, the current control strategy in the electrochemical can be obtained through the BPNN model. Finally, the proposed intelligent control strategy is applied to the electrochemical system for ammonia removal, which can reduce the negative impact of water quality changes and reduce energy consumption by 38% compared with the original strategy.