This paper presents a novel two-phased and Ensemble scheme integrated Backpropagation (TP-ES-BP) algorithm, which could greatly alleviate the problem of local minima of standard BP (SBP) algorithm, and overcome the limitations of individual component BPs in classification performance by the integration of Ensemble method. Empirical and t-test results of three groups of simulation experiments, including the face recognition task on ORL face image database and four benchmark classification tasks on datasets drawn from the UCI repository of machine learning databases, show that TP-ES-BP algorithm achieves significantly better recognition results and higher generalization performance compared to SBP and the state-of-the-art emotional backpropagation (EmBP) learning algorithm. 
A two-phased and Ensemble scheme integrated Backpropagation algorithm