Title: Hybrid intelligence model on the second generation neural network

Authors: Amit Gupta; Vikash Yadav; Bipin Kumar Tripathi; Vivek Srivastava

Addresses: Department of Computer Science and Engineering, Dr. A.P.J. Abdul Kalam Technical University, Lucknow, India ' Department of Computer Science and Engineering, ABES Engineering College, Ghaziabad, India ' Department of Computer Science and Engineering, Harcourt Butler Technical University, Kanpur, India ' Department of Computer Science and Engineering, Rama University, Kanpur, India

Abstract: In latest beyond, it has been visualised in various neural computing applications that the hybridisation of computational intelligence techniques yields better results over traditional methods. This proposed research introduces a new composite version (hybrid) computational model in both real and complex domain that is a unique fusion of revised evolutionary fuzzy clustering along with correlated neural networks. The whole methodology is based on two type of working framework as fuzzy assessment framework and neural categoriser framework. In first framework, suggest styles are disbursed as according to the quantity of clusters on the basis of learning strategy like revised evolutionary fuzzy clustering for generalisation of various evaluated cluster patterns that is totally responsible for selection process of network structure. The second framework of the proposed strategy is to fully based on the correlated neural network evolving the processes of training and subsequent generalisation. The existing real domain analysis is based on first generation neural network (RVNN) and for the analysis of proposed model in second generation neural network (CVNN), Hilbert transformation is used that is available in MATLAB for converting the real datasets in complex form.

Keywords: hybrid computational intelligence (real and complex); complex evolutionary computation; second generation neural network; 2DNN/CVNN; Hilbert transformation; fuzzy clustering.

DOI: 10.1504/IJAIP.2021.113334

International Journal of Advanced Intelligence Paradigms, 2021 Vol.18 No.3, pp.398 - 416

Received: 02 Jul 2018
Accepted: 26 Oct 2018
Published online: 01 Mar 2021 *

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