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On comparing the performances of MLP and RBFN on sales forecasting problem

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Abstract

This paper addresses the problem of predicting the sales by develo** two sales forecasting models based on multi-layered perceptron (MLP) and radial basis function network (RBFN). The performance of both these models have been thoroughly compared in predicting the sales. To update the parameters in these models we have used dynamic back-propagation (DBP) method. Simulation results obtained shows that MLP has performed better than the RBFN.

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Authors and Affiliations

  1. Faculty of Management Studies, Manav Rachna University, Faridabad, India

    Raman Tiwari

  2. Department of Electrical and Instrumentation Engineering, Thapar Institute of Engineering and Technology, Patiala, 147004, India

    Rajesh Kumar

  3. Faculty of Management Studies, Manav Rachna International Institute of research and studies, Faridabad, India

    Rajat Gera

  4. Division of Instrumentation and Control, Netaji Subhas University of Technology (formerly Netaji Subhas Institute of Technology), New Delhi, 110078, India

    Smriti Srivastava

Authors
  1. Raman Tiwari
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  2. Rajesh Kumar
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  3. Rajat Gera
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  4. Smriti Srivastava
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Correspondence to Smriti Srivastava.

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Tiwari, R., Kumar, R., Gera, R. et al. On comparing the performances of MLP and RBFN on sales forecasting problem. Int. j. inf. tecnol. 14, 301–309 (2022). https://doi.org/10.1007/s41870-019-00402-x

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  • DOI: https://doi.org/10.1007/s41870-019-00402-x

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