The algorithm of incremental learning in cover based constructive neural networks (CBCNN) is investigated by using BiCovering algorithm (BiCA) in this paper. This incremental learning algorithm based on the idea of CBCNN can set up many postive-covers and negative-covers, and can modify and optimize the parameters and structure of the neural networks continuously, and can add the nodes according to the need and prune the redundant nodes. BiCA algorithm not only keep the advantages of CBCNN but also fit for incremental learning and could enhance the generalization capability of the neural networks. The simulational results show that the BiCA algorithm is not sensitive to the order of the sample and could learn quickly and steady even if the performance of initial CBCNN is not very good.