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A Novel Group Teaching Optimization Algorithm Based Artificial Neural Network for Classification

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Intelligent Technologies and Applications (INTAP 2021)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1616))

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Abstract

Traditional techniques of training Artificial Neural Networks (ANNs) i.e. the Back Propagation algorithm (BPA), have high computational time and number of iterations and hence have been improved over the years with the induction of meta-heuristic algorithms that introduce randomness into the training process but even they have been seen to be prone to falling into local minima cost solutions at high dimensional search space and/or have low convergence rate. To cater for the inefficiencies of training such an ANN, a novel neural network classifier is presented in this paper using the simulation of the group teaching mechanism to update weights and biases of the neural network. The proposed network, the group teaching optimization algorithm based neural network (GTOA-NN) consists of an input layer, a single hidden layer of 10 neurons, and an output layer. Two University of California Irvine (UCI) database sample datasets have been used as benchmark for this study, namely ‘Iris’ and ‘Blood Transfusion Service Center’, for which the training accuracy is 97% and 77.9559% whereas the testing accuracy is 98% and 83.5341% respectively. Comparative analysis with PSO-NN and GWO-NN unveil that the proposed GTOA-NN outperforms by 0.4% and 4% in training accuracy and 2.6% and 6.8% in testing accuracy respectively.

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Author information

Authors and Affiliations

  1. National University of Sciences and Technology, Islamabad, Pakistan

    Syed Kumayl Raza Moosavi, Hassaan Bin Younis, Malik Naveed Akhter & Shahzaib Farooq Hadi

  2. Capital University of Science and Technology, Islamabad, Pakistan

    Muhammad Hamza Zafar

  3. Northwestern Polytechnical University, Xian, China

    Haider Ali

Authors
  1. Syed Kumayl Raza Moosavi
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  2. Hassaan Bin Younis
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  3. Muhammad Hamza Zafar
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  4. Malik Naveed Akhter
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  5. Shahzaib Farooq Hadi
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  6. Haider Ali
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Corresponding author

Correspondence to Syed Kumayl Raza Moosavi .

Editor information

Editors and Affiliations

  1. University of Agder (UiA), Grimstad, Norway

    Filippo Sanfilippo

  2. University of Agder (UiA), Grimstad, Norway

    Ole-Christoffer Granmo

  3. Norwegian University of Science and Technology (NTNU), Gjøvik, Norway

    Sule Yildirim Yayilgan

  4. The Islamia University of Bahawalpur (IUB), Bahawalpur, Pakistan

    Imran Sarwar Bajwa

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Moosavi, S.K.R., Younis, H.B., Zafar, M.H., Akhter, M.N., Hadi, S.F., Ali, H. (2022). A Novel Group Teaching Optimization Algorithm Based Artificial Neural Network for Classification. In: Sanfilippo, F., Granmo, OC., Yayilgan, S.Y., Bajwa, I.S. (eds) Intelligent Technologies and Applications. INTAP 2021. Communications in Computer and Information Science, vol 1616. Springer, Cham. https://doi.org/10.1007/978-3-031-10525-8_5

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  • DOI: https://doi.org/10.1007/978-3-031-10525-8_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-10524-1

  • Online ISBN: 978-3-031-10525-8

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