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  Robust Prediction Capability of Feed Forward Back Propagation Network over Adaptive Neuro Fuzzy Inference System on Optical Characteristics of Ironbased Superconductor Glass materials  
  Authors : Anindita Das Bhattacharjee; Shibashis Mitra; Asiya Amreen Zaman
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This research intends to establish the dominant prediction potentiality of Feed Forward Back Propagation Networks over the Adaptive Neuro Fuzzy Inference Systems. The elementary step contains the analysis on the different transfer functions of Feed Forward Back Propagation Network in order to identify the most convenient transfer function for estimating optical parameters of Fe doped Glass material: real parts of Absorption Co-efficient and Refractive Index over Wavelength. The motive behind Fe doping is that it converts Glass material which acts as a Semiconductor to behave as a Superconductor which eventualizes its high applicability in the field of Telecommunication, Optoelectronics, Laser Based Manufacturing, Biomedical Engineering and more. Further, Adaptive Neuro Fuzzy Inference System with different membership functions are examined to reach best probable outcome. The optical properties in the basic experimental dataset are studied using Spin coater and Ultraviolet Spectrometer ranging in between 29.3 µg/cm2 to 2623 µg/cm2, whereas, only two samples are considered in this research paper among the given five samples.


Published In : IJCSN Journal Volume 7, Issue 3

Date of Publication : June 2018

Pages : 166-181

Figures :28

Tables : 19


Anindita Das Bhattacharjee : started her career in industry as a trainee software developer for a year. She has done M. Tech in Computer Science from National Institute of Technology (NIT), Durgapur. She secured a position of First Class Second in M. Tech. Currently she is working in Swami Vivekananda Institute of Science and Technology. She has been teaching for about 10 years in Computer Science. She is an author of a book “Artificial Intelligence and Soft Computing for Beginners” published in 2013 and author of book chapters in the book “Intelligent Analysis for Multimedia Information” published by IGI Global and indexed in Scopus.

Shibashis Mitra : is pursuing B. Tech. Final year student in Computer Science and Engineering in Swami Vivekananda Institute of Science and Technology.

Asiya Amreen Zaman : is pursuing B. Tech. Final year student in Computer Science and Engineering in Swami Vivekananda Institute of Science and Technology. Secured 3rd position in International Olympiad of Science and 2nd position in Olympiad of English 2011, New Delhi.


Absorption Co-efficient, Adaptive Neuro- Fuzzy Inference System, Refractive Index, Regression, Semiconductor Doping, Superconductor

In order to develop a robust decision-making model, a Hybrid Model (ANFIS) which incorporates the property of parallelism in computing of a Neural Network along with inference capability of Fuzzy Logic Designer is used in the comparative analysis but FFBPN still outperforms the hybrid model ANFIS due to some of its inherent behavioural properties and also depends upon the nature of preferred input dataset.


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