Building Ensemble Classifier Based on Complex Network for Predicting Protein Structural Class

Abstract

Abstract. In recent years, complex network models were developed to solve classification and time series prediction problems. In this paper, ensemble classifier based on complex network (mainly scale-free network) is firstly used to predict protein structural class. For the classifier design, genetic programming and particle swarm optimization algorithm are used alternately to evolve the structure and encoding parameters. The experimental results validate the good performance of the proposed method.

Pixel‐wise skin colour detection based on flexible neural tree

“…The FNT showed good performance in prediction [12,13,36]. Based on FNT and our previous work [14,15,37], a FNT-based skin colour model is proposed to address the problem of selection of colour spaces and improving performance in skin colour detection.…”