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Biological Data Analysis Using Hybrid Functional Link Artificial Neural Network

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Swarm, Evolutionary, and Memetic Computing (SEMCCO 2014)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8947))

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Abstract

With rapid growth in field of medical sciences; biologists have stepped up and had discovered many biological characteristics for different diseases. There are many issues involved in knowledge discovery from these huge biomedical data for useful medical application. Traditional algorithms for neural network such as multi-layer perceptron model have proven to be inefficient for the classification of different biological data, as in many cases to get a better classifier we have to increase number of layers in simple artificial neural network which increases the complexity of the network. In contrast to multiple layer perceptron networks, Functional Link Artificial Neural Network (FLANN) can be implemented for the task of data classification with reduced complexity. In this proposed paper work an experimental study has been presented where a simple FLANN based classification model is compared with Hybrid FLANN models. In the first hybrid model an optimization technique i.e. Particle Swarm Optimization (PSO) is applied along with FLANN for weight updation. Then in the second hybrid FLANN model a feature selection technique i.e. Signal to Noise Ratio (SNR) is applied. Finally the classification accuracies are compared for the estimation of good performances.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Information Technology, Institute of Technical Education and Research, Siksha o Anusandhan University, Khandagiri Square, Bhubaneswar, India

    Manaswini Jena & Rasmita Dash

  2. Department of Computer Science and Engineering, Silicon Institute of Technology, Bhubaneswar, 751024, Odisha, India

    Bijan Bihari Misra

Authors
  1. Manaswini Jena
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  2. Rasmita Dash
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  3. Bijan Bihari Misra
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Corresponding author

Correspondence to Manaswini Jena .

Editor information

Editors and Affiliations

  1. Department of Electrical Engineering, IIT, New Delhi, India

    Bijaya Ketan Panigrahi

  2. School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore

    Ponnuthurai Nagaratnam Suganthan

  3. Electronics and Communication Sciences Unit, Indian Statistical Institute, Kolkata, India

    Swagatam Das

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Jena, M., Dash, R., Misra, B.B. (2015). Biological Data Analysis Using Hybrid Functional Link Artificial Neural Network. In: Panigrahi, B., Suganthan, P., Das, S. (eds) Swarm, Evolutionary, and Memetic Computing. SEMCCO 2014. Lecture Notes in Computer Science(), vol 8947. Springer, Cham. https://doi.org/10.1007/978-3-319-20294-5_8

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  • DOI: https://doi.org/10.1007/978-3-319-20294-5_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-20293-8

  • Online ISBN: 978-3-319-20294-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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