Hybrid intelligence model on the second generation neural network
by Amit Gupta; Vikash Yadav; Bipin Kumar Tripathi; Vivek Srivastava
International Journal of Advanced Intelligence Paradigms (IJAIP), Vol. 18, No. 3, 2021

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.

Online publication date: Mon, 01-Mar-2021

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Advanced Intelligence Paradigms (IJAIP):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com