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Fortified Cuckoo Search Algorithm on training multi-layer perceptron for solving classification problems

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Abstract

Multi-layer perceptron (MLP) in artificial neural networks (ANN) is one among the trained neural models which can hold several layers as a hidden layer for intensive training to obtain optimal results. On the other hand, the classification problem has a high level of attraction towards researchers to increase the accuracy in classification. In ANN, feedforward neural network (FNN) is one model that possesses the art of solving classification and regression problems. When input data is given to FNN, it will apply the sum of product rule and the activation function to map the input with its appropriate output. In the sum of product rule, a term called weights is to be chosen appropriately to map between the input and output. In standard FNN, the weights are chosen in a random way which may lead to slower convergence towards the optimal choice of weight values. In this paper, an effective optimization model is proposed to optimize the weights of MLP of FNN for effective classification problems. Four different datasets were chosen, and the results are interpreted with statistical performance measures.

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Authors and Affiliations

  1. Centre for Smart Grid Technologies, School of Computer Science and Engineering, Vellore Institute of Technology, Chennai Campus, Tami Nadu, Chennai, 600127, India

    Kalaipriyan Thirugnanasambandam

  2. Department of Computer Science and Engineering, Velagapudi Ramakrishna Siddhartha Engineering College, Vijayawada, Andhra Pradesh, 520007, India

    U. Prabu

  3. Department of Computer Science Engineering, VIT Bhopal University, Bhopal-Indore Highway, Bhopal, Madhya Pradesh, 466114, India

    D. Saravanan

  4. Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur, Andhra Pradesh, 522302, India

    Dinesh Kumar Anguraj

  5. School of Computing, SASTRA Deemed University, Thanjavur, Tamil Nadu, 613007, India

    R.S. Raghav

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  1. Kalaipriyan Thirugnanasambandam
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  2. U. Prabu
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  3. D. Saravanan
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  4. Dinesh Kumar Anguraj
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  5. R.S. Raghav
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Correspondence to R.S. Raghav.

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Thirugnanasambandam, K., Prabu, U., Saravanan, D. et al. Fortified Cuckoo Search Algorithm on training multi-layer perceptron for solving classification problems. Pers Ubiquit Comput 27, 1039–1049 (2023). https://doi.org/10.1007/s00779-023-01716-1

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