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Principal Component Analysis Enhanced Multi-layer Perceptron for Multi-economic Indicators in Southern African Economic Prediction

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Software Engineering Perspectives in Intelligent Systems (CoMeSySo 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1295))

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Abstract

Economic growth may be determined based on different economic parameters. The main purpose of this research work is to predict economic growth based on several economic indicators. In this study, an enhanced Multi-layer Perceptron (MLP) model is built and the prediction performances are evaluated and compared with existing models. Using the Principal Component Analysis technique, major contributing indicators where identified and passed as input to tne MLP input layer. Results show a better performance by the PCA enhanced MLP with consistent accuracy as time-step increases. Furthermore, drop in GDP over the first 3 time-step and improvement in the last 3 time-step can be observed.

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Authors and Affiliations

  1. Department of ICT, Faculty of Applied and Computer Science, Vaal University of Technology, Andries Potgieter Blvd, Vanderbijlpark, 1900, South Africa

    Moses Olaifa & Tranos Zuva

Authors
  1. Moses Olaifa
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  2. Tranos Zuva
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Correspondence to Moses Olaifa .

Editor information

Editors and Affiliations

  1. Faculty of Applied Informatics, Tomas Bata University in Zlín, Zlín, Czech Republic

    Radek Silhavy

  2. Faculty of Applied Informatics, Tomas Bata University in Zlín, Zlín, Czech Republic

    Petr Silhavy

  3. Faculty of Applied Informatics, Tomas Bata University in Zlín, Zlín, Czech Republic

    Zdenka Prokopova

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Olaifa, M., Zuva, T. (2020). Principal Component Analysis Enhanced Multi-layer Perceptron for Multi-economic Indicators in Southern African Economic Prediction. In: Silhavy, R., Silhavy, P., Prokopova, Z. (eds) Software Engineering Perspectives in Intelligent Systems. CoMeSySo 2020. Advances in Intelligent Systems and Computing, vol 1295. Springer, Cham. https://doi.org/10.1007/978-3-030-63319-6_63

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