Solving nonlinear classification problems with black hole optimisation and higher order Jordan Pi-sigma neural network: a novel approach
Bighnaraj Naik, Himansu Sekhar Behera, Janmenjoy Nayak · International Journal of Computational Systems Engineering · 2016
Nature inspired optimisation algorithms have been on a leading focus of all researchers since last few decades. Successful applications of such algorithms for solving diversified problem domains make them more popular. This presented research is about to implement a novel nature inspired algorithm with higher order neural network for solving nonlinear classification problems of data mining. A recently developed nature inspired algorithm, black hole optimisation has been used to train the weights of a higher order Jordan Pi-sigma neural network and to optimise the performance of the network. The proposed black hole algorithm-based higher order neural network has been developed for solving the classification problems in data mining. The result of the proposed method is compared with some other benchmark meta-heuristic techniques like PSO, GA and found that the proposed method is superior to other approaches.