Publication Type : Conference Proceedings
Publisher : IEEE
Source : Fifth International Conference on Electrical, Computer and Communication Technologies (ICECCT)
Url : https://ieeexplore.ieee.org/abstract/document/10179833
Campus : Amritapuri
School : School of Physical Sciences
Department : Mathematics
Year : 2023
Abstract : ChaosNet is a type of artificial neural network framework developed for classification problems and is influenced by the chaotic property of the human brain. Each neuron of the ChaosNet architecture is the one-dimensional chaotic map called the Generalized Luröth Series (GLS). The addition of GLS as neurons in ChaosNet makes the computations straightforward while utilizing the advantageous elements of chaos. With substan-tially less data, ChaosNet has been demonstrated to do difficult classification problems on par with or better than traditional ANNs. In this paper, we use Chaosnet to perform a functional classification of Hypothetical proteins [HP], which is indeed a topic of great interest in bioinformatics. The results obtained with significantly lesser training data are compared with the standard machine learning techniques used in the literature.
Cite this Research Publication : S Hari, A Sudeesh, PP Nair, P Suravajhala, Biologically inspired ChaosNet architecture for Hypothetical Protein Classification, Fifth International Conference on Electrical, Computer and Communication Technologies (ICECCT), 2023.